If you have not yet registered your protocol, you can benefit of our tools to select a priori the type of input data that could be extracted to estimate an effect size.
hierarch_name | name_input_data | list_input_data | corresponding_R_function | natural_effect_size_measure | converted_effect_size_measure | adjusted_input_data |
---|
hierarch_name | name_input_data | list_input_data | corresponding_R_function | natural_effect_size_measure | converted_effect_size_measure | adjusted_input_data | |
---|---|---|---|---|---|---|---|
37 | or_se | Odds ratio value + standard error | Section 2. https://metaconvert.org/html/input.html | es_from_or_se() | OR | RR+NNT+D+G+R+Z | Non-adjusted |
38 | or_ci | Odds ratio value + 95% confidence interval | Section 2. https://metaconvert.org/html/input.html | es_from_or_ci() | OR | RR+NNT+D+G+R+Z | Non-adjusted |
39 | or_pval | Odds ratio value + p-value | Section 2. https://metaconvert.org/html/input.html | es_from_or_pval() | OR | RR+NNT+D+G+R+Z | Non-adjusted |
40 | 2x2 | Number of participants in each cell of a 2x2 table | Section 7. https://metaconvert.org/html/input.html | es_from_2x2() | OR+RR+NNT | D+G+R+Z | Non-adjusted |
41 | 2x2_sum | Number of participants 'developping the disease' and row marginal sums | Section 7. https://metaconvert.org/html/input.html | es_from_2x2_sum() | OR+RR+NNT | D+G+R+Z | Non-adjusted |
42 | 2x2_prop | Proportion of participants 'developping the disease' and row marginal proportions | Section 7. https://metaconvert.org/html/input.html | es_from_2x2_prop() | OR+RR+NNT | D+G+R+Z | Non-adjusted |
45 | chisq | Chi-square value (obtained from a 2x2 table) | Section 8. https://metaconvert.org/html/input.html | es_from_chisq() | OR+RR+R+Z | D+G | Non-adjusted |
46 | phi | Phi coefficient | Section 8. https://metaconvert.org/html/input.html | es_from_phi() | OR+RR+R+Z | D+G | Non-adjusted |
47 | chisq_pval | P-value of a Chi-square (obtained from a 2x2 table) | Section 8. https://metaconvert.org/html/input.html | es_from_chisq_pval() | OR+RR+R+Z | D+G | Non-adjusted |
study_id | author | year | predictor | outcome | all_info_expected | n_exp | n_nexp | n_cases | n_controls | reverse_2x2 | baseline_risk | small_margin_prop | n_cases_exp | n_cases_nexp | n_controls_exp | n_controls_nexp | reverse_prop | prop_cases_exp | prop_cases_nexp | reverse_chisq | chisq | reverse_chisq_pval | chisq_pval | reverse_phi | phi | reverse_or | or | logor | logor_se | or_ci_lo | or_ci_up | logor_ci_lo | logor_ci_up | reverse_or_pval | or_pval | reverse_rr | rr | logrr | logrr_se | rr_ci_lo | rr_ci_up | logrr_ci_lo | logrr_ci_up | reverse_rr_pval | rr_pval | user_es_measure_crude | user_es_crude | user_se_crude | user_ci_lo_crude | user_ci_up_crude | user_es_measure_adj | user_es_adj | user_se_adj | user_ci_lo_adj | user_ci_up_adj |
---|
study_id | author | year | predictor | outcome | all_info_expected | n_exp | n_nexp | n_cases | n_controls | reverse_2x2 | baseline_risk | small_margin_prop | n_cases_exp | n_cases_nexp | n_controls_exp | n_controls_nexp | reverse_prop | prop_cases_exp | prop_cases_nexp | reverse_chisq | chisq | reverse_chisq_pval | chisq_pval | reverse_phi | phi | reverse_or | or | logor | logor_se | or_ci_lo | or_ci_up | logor_ci_lo | logor_ci_up | reverse_or_pval | or_pval | reverse_rr | rr | logrr | logrr_se | rr_ci_lo | rr_ci_up | logrr_ci_lo | logrr_ci_up | reverse_rr_pval | rr_pval | user_es_measure_crude | user_es_crude | user_se_crude | user_ci_lo_crude | user_ci_up_crude | user_es_measure_adj | user_es_adj | user_se_adj | user_ci_lo_adj | user_ci_up_adj | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | unique ID for each study - numeric/character | first author name - numeric/character | year of publication - numeric/character | intervention/exposure - numeric/character | outcome - numeric/character | expected input data leading to an effect size estimate - character | number of participants in the exposed/experimental group - numeric | number of participants in the non-exposed/non-experimental group - numeric | number of cases/events across exposed/non-exposed groups - numeric | number of controls/no-event across exposed/non-exposed groups - numeric | whether the direction of the effect size generated from the contingency table should be flipped - logical | proportion of cases/events in the non-exposed group - numeric | smallest margin proportion of cases/events in the underlying 2x2 table - numeric | number of cases/events in the exposed group - numeric | number of cases/events in the non exposed group - numeric | number of controls/no-event in the exposed group - numeric | number of controls/no-event in the non exposed group - numeric | whether the direction of the cohen_d value should be flipped - logical | proportion of cases/events in the exposed group (ranging from 0 to 1) - numeric | proportion of cases/events in the non-exposed group (ranging from 0 to 1) - numeric | whether the direction of the effect size generated from the chi-square value should be flipped - logical | chi-square value - numeric | whether the direction of the effect size generated from the chi-square p-value should be flipped - logical | chi-square p-value - numeric | whether the direction of the effect size generated from the phi value should be flipped - logical | phi value - numeric | whether the direction of the effect size generated from the odds ratio should be flipped - logical | odds ratio value - numeric | log odds ratio value - numeric | standard error of the log odds ratio - numeric | lower bound of the 95% CI of the risk ratio - numeric | upper bound of the 95% CI of the log risk ratio - numeric | lower bound of the 95% CI of the risk ratio - numeric | upper bound of the 95% CI of the log risk ratio - numeric | whether the direction of the cohen_d value should be flipped - logical | p-value of an odds ratio - numeric | whether the direction of the effect size generated from the risk ratio should be flipped - logical | risk ratio value - numeric | log risk ratio value - numeric | log risk ratio standard error - numeric | lower bound of the 95% CI of the risk ratio - numeric | upper bound of the 95% CI of the risk ratio - numeric | lower bound of the 95% CI of the log risk ratio - numeric | upper bound of the 95% CI of the log risk ratio - numeric | whether the direction of the risk ratio generated from a p-value should be flipped - logical | p-value of a risk ratio - numeric | name of the (non-adjusted) effect size measure used - character | value of an effect size - numeric | standard error of the effect size - numeric | lower bound of the 95% CI of the effect size measure - numeric | upper bound of the 95% CI of the effect size measure - numeric | name of the (adjusted) effect size measure used - character | value of the adjusted effect size - numeric | standard error of the effect size - numeric | adjusted lower bound of the 95% CI of the effect size measure - numeric | adjusted upper bound of the 95% CI of the effect size measure - numeric |
When data extraction has been performed in duplicate, our tools offer the possibility to flag the differences between the two datasets. For this example, we will use two datasets (df.compare1 and df.compare2) distributed with metaConvert.
rowname | chng_type | study_id | author | year | n_exp | n_nexp | prop_cases_exp | prop_cases_nexp |
---|---|---|---|---|---|---|---|---|
1 | df_extractor_1 | 1 | Michellini | 2000 | 20 | 40 | 0.2 | 0.2 |
1 | df_extractor_2 | 1 | Smith | 2000 | 20 | 40 | 0.2 | 0.2 |
2 | df_extractor_1 | 2 | Jones | 2019 | 52 | 32 | 0.44 | 0.34 |
2 | df_extractor_2 | 2 | Vietillini | 2019 | 52 | 32 | 0.44 | 0.34 |
3 | df_extractor_1 | 3 | Raymond | 2022 | 198 | 238 | 0.32 | 0.22 |
3 | df_extractor_2 | 3 | Raymond | 2020 | 188 | 238 | 0.32 | 0.22 |
4 | df_extractor_1 | 4 | El-Jiher | 2017 | 2010 | 1991 | 0.1 | 0.21 |
4 | df_extractor_2 | 4 | El-Jiher | 2017 | 2010 | 1991 | 0.1 | 0.31 |
5 | df_extractor_1 | 5 | Tortolinni | 2005 | 111 | 181 | 0.5 | 0.45 |
5 | df_extractor_2 | 5 | Tortolinni | 2005 | 111 | 181 | 0.5 | 0.4 |
6 | df_extractor_2 | 3 | Raymond | 2022 | 198 | 10 | 0.32 | 0.22 |
In grey, values that are consistent between the two data extractors. In green/red, the values that differ.
Only rows with differences between the two datasets are identified, and you can easily retrieve the row number by looking at the ID in the rowname column. If your dataset have rows in a different order (like in the example above), you can automatically reorder your datasets by indicating to the function the columns that store this information
compare_df(
df_extractor_1 = df.compare1,
df_extractor_2 = df.compare2,
ordering_columns = c("author", "year"),
output = "html")
rowname | chng_type | study_id | author | year | n_exp | n_nexp | prop_cases_exp | prop_cases_nexp | ID_metaConvert |
---|---|---|---|---|---|---|---|---|---|
1 | df_extractor_1 | 4 | El-Jiher | 2017 | 2010 | 1991 | 0.1 | 0.21 | El-Jiher_2017 |
1 | df_extractor_2 | 4 | El-Jiher | 2017 | 2010 | 1991 | 0.1 | 0.31 | El-Jiher_2017 |
2 | df_extractor_1 | 2 | Jones | 2019 | 52 | 32 | 0.44 | 0.34 | Jones_2019 |
2 | df_extractor_2 | ||||||||
3 | df_extractor_1 | 1 | Michellini | 2000 | 20 | 40 | 0.2 | 0.2 | Michellini_2000 |
3 | df_extractor_2 | ||||||||
4 | df_extractor_1 | ||||||||
4 | df_extractor_2 | 3 | Raymond | 2020 | 188 | 238 | 0.32 | 0.22 | Raymond_2020 |
5 | df_extractor_1 | 3 | Raymond | 2022 | 198 | 238 | 0.32 | 0.22 | Raymond_2022 |
5 | df_extractor_2 | 3 | Raymond | 2022 | 198 | 10 | 0.32 | 0.22 | Raymond_2022 |
6 | df_extractor_1 | ||||||||
6 | df_extractor_2 | 1 | Smith | 2000 | 20 | 40 | 0.2 | 0.2 | Smith_2000 |
7 | df_extractor_1 | 5 | Tortolinni | 2005 | 111 | 181 | 0.5 | 0.45 | Tortolinni_2005 |
7 | df_extractor_2 | 5 | Tortolinni | 2005 | 111 | 181 | 0.5 | 0.4 | Tortolinni_2005 |
8 | df_extractor_1 | ||||||||
8 | df_extractor_2 | 2 | Vietillini | 2019 | 52 | 32 | 0.44 | 0.34 | Vietillini_2019 |
For this example, we will generate effect sizes from the df.short dataset, and we will estimate Hedges’ g.
res = convert_df(x = df.short, measure = "g")
#> Warning in convert_df(x = df.short, measure = "g"): When you enter input data
#> that cannot be negative (F-test, eta-squared, p-value, or chi-square values),
#> do not forget to properly set up the direction of the generated effect size
#> using corresponding reverse_* argument!
row_id | study_id | author | year | outcome | all_info_crude | measure_crude | info_measure_crude | n_estimations_crude | es_selected_crude | info_used_crude | es_crude | se_crude | es_ci_lo_crude | es_ci_up_crude | min_info_crude | min_es_value_crude | min_es_se_crude | min_es_ci_lo_crude | min_es_ci_up_crude | max_info_crude | max_es_value_crude | max_es_se_crude | max_es_ci_lo_crude | max_es_ci_up_crude | diff_min_max_crude | overlap_min_max_crude | dispersion_es_crude | all_info_adjusted | measure_adjusted | info_measure_adjusted | n_estimations_adjusted | es_selected_adjusted | info_used_adjusted | es_adjusted | se_adjusted | es_ci_lo_adjusted | es_ci_up_adjusted | min_info_adjusted | min_es_value_adjusted | min_es_se_adjusted | min_es_ci_lo_adjusted | min_es_ci_up_adjusted | max_info_adjusted | max_es_value_adjusted | max_es_se_adjusted | max_es_ci_lo_adjusted | max_es_ci_up_adjusted | diff_min_max_adjusted | overlap_min_max_adjusted | dispersion_es_adjusted | id | type_publication | factor | n_exp | n_nexp | mean_exp | mean_sd_exp | mean_se_exp | mean_nexp | mean_sd_nexp | mean_se_nexp | mean_ci_lo_exp | mean_ci_up_exp | mean_ci_lo_nexp | mean_ci_up_nexp | md | md_se | student_t_pval | cohen_d | etasq | etasq_partial | cohen_d_adj | etasq_adj | n_cov_etasq | cov_outcome_etasq | n_cov_ancova | cov_outcome_r | ancova_mean_exp | ancova_mean_sd_exp | ancova_mean_se_exp | ancova_mean_nexp | ancova_mean_sd_nexp | ancova_mean_se_nexp | ancova_mean_ci_lo_exp | ancova_mean_ci_up_exp | ancova_mean_ci_lo_nexp | ancova_mean_ci_up_nexp | ancova_f | n_cases | n_controls | n_sample | prop_cases_exp | prop_cases_nexp | n_cases_exp | n_controls_exp | n_cases_nexp | n_controls_nexp | med_exp | q1_exp | q3_exp | med_nexp | q1_nexp | q3_nexp | min_exp | max_exp | min_nexp | max_nexp | anova_f | student_t | chisq | plot_mean_exp | plot_mean_sd_lo_exp | plot_mean_sd_up_exp | plot_mean_se_lo_exp | plot_mean_se_up_exp | plot_mean_ci_lo_exp | plot_mean_ci_up_exp | plot_mean_nexp | plot_mean_sd_lo_nexp | plot_mean_sd_up_nexp | plot_mean_se_lo_nexp | plot_mean_se_up_nexp | plot_mean_ci_lo_nexp | plot_mean_ci_up_nexp | plot_ancova_mean_exp | plot_ancova_mean_sd_lo_exp | plot_ancova_mean_sd_up_exp | plot_ancova_mean_se_lo_exp | plot_ancova_mean_se_up_exp | plot_ancova_mean_ci_lo_exp | plot_ancova_mean_ci_up_exp | plot_ancova_mean_nexp | plot_ancova_mean_sd_lo_nexp | plot_ancova_mean_sd_up_nexp | plot_ancova_mean_se_lo_nexp | plot_ancova_mean_se_up_nexp | plot_ancova_mean_ci_lo_nexp | plot_ancova_mean_ci_up_nexp | reverse_means | reverse_ancova_means | reverse_plot_means | reverse_plot_ancova_means | reverse_ancova_f | reverse_med | reverse_d | reverse_etasq | reverse_student_t | reverse_anova_f | reverse_chisq | reverse_2x2 | reverse_prop | dup | info_measure_crude.1 | info_measure_adjusted.1 | IDdef | user_es_measure_crude | user_es_crude | user_se_crude | user_ci_lo_crude | user_ci_up_crude | reverse_g | hedges_g | reverse_beta_std | beta_std | reverse_beta_unstd | beta_unstd | sd_dv | reverse_md | md_sd | md_ci_lo | md_ci_up | md_pval | mean_sd_pooled | reverse_student_t_pval | reverse_anova_f_pval | anova_f_pval | reverse_pt_bis_r | pt_bis_r | reverse_pt_bis_r_pval | pt_bis_r_pval | reverse_means_pre_post | mean_pre_exp | mean_pre_nexp | mean_pre_sd_exp | mean_pre_sd_nexp | mean_pre_se_exp | mean_pre_se_nexp | mean_pre_ci_lo_exp | mean_pre_ci_up_exp | mean_pre_ci_lo_nexp | mean_pre_ci_up_nexp | reverse_mean_change | mean_change_exp | mean_change_nexp | mean_change_sd_exp | mean_change_sd_nexp | mean_change_se_exp | mean_change_se_nexp | mean_change_ci_lo_exp | mean_change_ci_up_exp | mean_change_ci_lo_nexp | mean_change_ci_up_nexp | mean_change_pval_exp | mean_change_pval_nexp | r_pre_post_exp | r_pre_post_nexp | paired_t_exp | paired_t_nexp | reverse_paired_t | paired_t_pval_exp | paired_t_pval_nexp | reverse_paired_t_pval | paired_f_exp | paired_f_nexp | reverse_paired_f | paired_f_pval_exp | paired_f_pval_nexp | reverse_paired_f_pval | user_es_measure_adj | user_es_adj | user_se_adj | user_ci_lo_adj | user_ci_up_adj | ancova_mean_sd_pooled | reverse_ancova_t | ancova_t | reverse_ancova_t_pval | ancova_t_pval | reverse_ancova_f_pval | ancova_f_pval | reverse_ancova_md | ancova_md | ancova_md_sd | ancova_md_se | ancova_md_ci_lo | ancova_md_ci_up | ancova_md_pval | reverse_means_variability | reverse_means_change_variability | baseline_risk | small_margin_prop | reverse_or | or | logor | logor_se | or_ci_lo | or_ci_up | logor_ci_lo | logor_ci_up | reverse_or_pval | or_pval | reverse_rr | rr | logrr | logrr_se | rr_ci_lo | rr_ci_up | logrr_ci_lo | logrr_ci_up | reverse_rr_pval | rr_pval | reverse_chisq_pval | chisq_pval | reverse_phi | phi | reverse_pearson_r | pearson_r | reverse_fisher_z | fisher_z | unit_increase_iv | unit_type | sd_iv | time_exp | time_nexp | reverse_irr | discard | rr_to_or | or_to_rr | or_to_cor | smd_to_cor | pre_post_to_smd | cor_to_smd |
---|
row_id | study_id | author | year | outcome | all_info_crude | measure_crude | info_measure_crude | n_estimations_crude | es_selected_crude | info_used_crude | es_crude | se_crude | es_ci_lo_crude | es_ci_up_crude | min_info_crude | min_es_value_crude | min_es_se_crude | min_es_ci_lo_crude | min_es_ci_up_crude | max_info_crude | max_es_value_crude | max_es_se_crude | max_es_ci_lo_crude | max_es_ci_up_crude | diff_min_max_crude | overlap_min_max_crude | dispersion_es_crude | all_info_adjusted | measure_adjusted | info_measure_adjusted | n_estimations_adjusted | es_selected_adjusted | info_used_adjusted | es_adjusted | se_adjusted | es_ci_lo_adjusted | es_ci_up_adjusted | min_info_adjusted | min_es_value_adjusted | min_es_se_adjusted | min_es_ci_lo_adjusted | min_es_ci_up_adjusted | max_info_adjusted | max_es_value_adjusted | max_es_se_adjusted | max_es_ci_lo_adjusted | max_es_ci_up_adjusted | diff_min_max_adjusted | overlap_min_max_adjusted | dispersion_es_adjusted | id | type_publication | factor | n_exp | n_nexp | mean_exp | mean_sd_exp | mean_se_exp | mean_nexp | mean_sd_nexp | mean_se_nexp | mean_ci_lo_exp | mean_ci_up_exp | mean_ci_lo_nexp | mean_ci_up_nexp | md | md_se | student_t_pval | cohen_d | etasq | etasq_partial | cohen_d_adj | etasq_adj | n_cov_etasq | cov_outcome_etasq | n_cov_ancova | cov_outcome_r | ancova_mean_exp | ancova_mean_sd_exp | ancova_mean_se_exp | ancova_mean_nexp | ancova_mean_sd_nexp | ancova_mean_se_nexp | ancova_mean_ci_lo_exp | ancova_mean_ci_up_exp | ancova_mean_ci_lo_nexp | ancova_mean_ci_up_nexp | ancova_f | n_cases | n_controls | n_sample | prop_cases_exp | prop_cases_nexp | n_cases_exp | n_controls_exp | n_cases_nexp | n_controls_nexp | med_exp | q1_exp | q3_exp | med_nexp | q1_nexp | q3_nexp | min_exp | max_exp | min_nexp | max_nexp | anova_f | student_t | chisq | plot_mean_exp | plot_mean_sd_lo_exp | plot_mean_sd_up_exp | plot_mean_se_lo_exp | plot_mean_se_up_exp | plot_mean_ci_lo_exp | plot_mean_ci_up_exp | plot_mean_nexp | plot_mean_sd_lo_nexp | plot_mean_sd_up_nexp | plot_mean_se_lo_nexp | plot_mean_se_up_nexp | plot_mean_ci_lo_nexp | plot_mean_ci_up_nexp | plot_ancova_mean_exp | plot_ancova_mean_sd_lo_exp | plot_ancova_mean_sd_up_exp | plot_ancova_mean_se_lo_exp | plot_ancova_mean_se_up_exp | plot_ancova_mean_ci_lo_exp | plot_ancova_mean_ci_up_exp | plot_ancova_mean_nexp | plot_ancova_mean_sd_lo_nexp | plot_ancova_mean_sd_up_nexp | plot_ancova_mean_se_lo_nexp | plot_ancova_mean_se_up_nexp | plot_ancova_mean_ci_lo_nexp | plot_ancova_mean_ci_up_nexp | reverse_means | reverse_ancova_means | reverse_plot_means | reverse_plot_ancova_means | reverse_ancova_f | reverse_med | reverse_d | reverse_etasq | reverse_student_t | reverse_anova_f | reverse_chisq | reverse_2x2 | reverse_prop | dup | info_measure_crude.1 | info_measure_adjusted.1 | IDdef | user_es_measure_crude | user_es_crude | user_se_crude | user_ci_lo_crude | user_ci_up_crude | reverse_g | hedges_g | reverse_beta_std | beta_std | reverse_beta_unstd | beta_unstd | sd_dv | reverse_md | md_sd | md_ci_lo | md_ci_up | md_pval | mean_sd_pooled | reverse_student_t_pval | reverse_anova_f_pval | anova_f_pval | reverse_pt_bis_r | pt_bis_r | reverse_pt_bis_r_pval | pt_bis_r_pval | reverse_means_pre_post | mean_pre_exp | mean_pre_nexp | mean_pre_sd_exp | mean_pre_sd_nexp | mean_pre_se_exp | mean_pre_se_nexp | mean_pre_ci_lo_exp | mean_pre_ci_up_exp | mean_pre_ci_lo_nexp | mean_pre_ci_up_nexp | reverse_mean_change | mean_change_exp | mean_change_nexp | mean_change_sd_exp | mean_change_sd_nexp | mean_change_se_exp | mean_change_se_nexp | mean_change_ci_lo_exp | mean_change_ci_up_exp | mean_change_ci_lo_nexp | mean_change_ci_up_nexp | mean_change_pval_exp | mean_change_pval_nexp | r_pre_post_exp | r_pre_post_nexp | paired_t_exp | paired_t_nexp | reverse_paired_t | paired_t_pval_exp | paired_t_pval_nexp | reverse_paired_t_pval | paired_f_exp | paired_f_nexp | reverse_paired_f | paired_f_pval_exp | paired_f_pval_nexp | reverse_paired_f_pval | user_es_measure_adj | user_es_adj | user_se_adj | user_ci_lo_adj | user_ci_up_adj | ancova_mean_sd_pooled | reverse_ancova_t | ancova_t | reverse_ancova_t_pval | ancova_t_pval | reverse_ancova_f_pval | ancova_f_pval | reverse_ancova_md | ancova_md | ancova_md_sd | ancova_md_se | ancova_md_ci_lo | ancova_md_ci_up | ancova_md_pval | reverse_means_variability | reverse_means_change_variability | baseline_risk | small_margin_prop | reverse_or | or | logor | logor_se | or_ci_lo | or_ci_up | logor_ci_lo | logor_ci_up | reverse_or_pval | or_pval | reverse_rr | rr | logrr | logrr_se | rr_ci_lo | rr_ci_up | logrr_ci_lo | logrr_ci_up | reverse_rr_pval | rr_pval | reverse_chisq_pval | chisq_pval | reverse_phi | phi | reverse_pearson_r | pearson_r | reverse_fisher_z | fisher_z | unit_increase_iv | unit_type | sd_iv | time_exp | time_nexp | reverse_irr | discard | rr_to_or | or_to_rr | or_to_cor | smd_to_cor | pre_post_to_smd | cor_to_smd | |
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110 | 1 | el-Rad_2006 | el-Rad | 2006 | Facial emotion recognition | anova_f | g | anova_f | 1 | hierarchy | anova_f | 1.226 | 0.278 | 0.669 | 1.783 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | -- None available -- | 0 | hierarchy | 108 | Article | Facial emotion recognition | 30 | 30 | 60 | 23.15 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | el-Rad_2006_anova_f_-- None available -- | anova_f | el-Rad_2006anova_fNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
24 | 2 | Tolliver III_2021 | Tolliver III | 2021 | Everyday social skills | cohen_d | g | cohen_d | 1 | hierarchy | cohen_d | 0.683 | 0.176 | 0.335 | 1.032 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | -- None available -- | 0 | hierarchy | 44 | Article | Strengths and Difficulties Questionnaire (SDQ) | 53 | 92 | 0.687 | 145 | 3.095 | 1.94 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Tolliver III_2021_cohen_d_-- None available -- | cohen_d | Tolliver III_2021cohen_dNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
31 | 3 | Steiner-Otoo_2020 | Steiner-Otoo | 2020 | Facial emotion recognition | cohen_d + means_ci + student_t + variability_means_ci | g | cohen_d + means_ci + student_t | 3 | hierarchy | cohen_d | 1.025 | 0.286 | 0.451 | 1.599 | student_t | 1.02 | 0.286 | 0.446 | 1.593 | cohen_d | 1.025 | 0.286 | 0.451 | 1.599 | 0.005 | 0.991 | 0.003 | -- None available -- | 0 | hierarchy | 32 | Article | Child Affective Facial Expression set (CAFE) | 28 | 26 | 20.5 | 23.8 | 19 | 21.99 | 22.9 | 24.71 | 1.04 | 54 | 3.8 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Steiner-Otoo_2020_cohen_d + means_ci + student_t + variability_means_ci_-- None available -- | cohen_d + means_ci + student_t | Steiner-Otoo_2020cohen_d + means_ci + student_tNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
41 | 4 | al-Sinai_2017 | al-Sinai | 2017 | Theory of mind | cohen_d + means_sd + variability_means_sd | g | cohen_d + means_sd | 2 | hierarchy | cohen_d | -0.128 | 0.3 | -0.734 | 0.479 | means_sd | -0.134 | 0.3 | -0.741 | 0.473 | cohen_d | -0.128 | 0.3 | -0.734 | 0.479 | 0.006 | 0.99 | 0.004 | -- None available -- | 0 | hierarchy | 109 | Article | Theory of Mind (NEPSY-II) | 23 | 20 | 21 | 2.11 | 20.7 | 2.3 | 0.13 | 43 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | al-Sinai_2017_cohen_d + means_sd + variability_means_sd_-- None available -- | cohen_d + means_sd | al-Sinai_2017cohen_d + means_sdNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
51 | 5 | Huerta_2002 | Huerta | 2002 | Everyday social skills | cohen_d + means_sd + anova_f + variability_means_sd | g | cohen_d + means_sd + anova_f | 3 | hierarchy | cohen_d | 0.249 | 0.137 | -0.021 | 0.52 | means_sd | 0.235 | 0.137 | -0.035 | 0.505 | cohen_d | 0.249 | 0.137 | -0.021 | 0.52 | 0.014 | 0.948 | 0.007 | -- None available -- | 0 | hierarchy | 68 | Article | Child-reported self-perceptions (SPPC) | 195 | 73 | 2.89 | 0.74 | 3.06 | 0.67 | -0.25 | 268 | 3.11 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Huerta_2002_cohen_d + means_sd + anova_f + variability_means_sd_-- None available -- | cohen_d + means_sd + anova_f | Huerta_2002cohen_d + means_sd + anova_fNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
61 | 6 | Lopez_2019 | Lopez | 2019 | Everyday social skills | cohen_d + means_sd + means_se + means_ci + student_t + variability_means_sd + variability_means_se + variability_means_ci | g | cohen_d + means_sd + means_se + means_ci + student_t | 5 | hierarchy | cohen_d | 3.416 | 0.399 | 2.616 | 4.215 | student_t | 3.406 | 0.399 | 2.608 | 4.204 | means_se | 3.417 | 0.4 | 2.618 | 4.217 | 0.011 | 0.986 | 0.005 | -- None available -- | 0 | hierarchy | 139 | Conférence | Social Responsiveness Scale (SRS) | 31 | 30 | 60.29 | 13.56 | 2.43 | 21.8 | 7.91 | 1.44 | 55.32 | 65.26 | 18.84 | 24.76 | 3.46 | 61 | 13.47 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Lopez_2019_cohen_d + means_sd + means_se + means_ci + student_t + variability_means_sd + variability_means_se + variability_means_ci_-- None available -- | cohen_d + means_sd + means_se + means_ci + student_t | Lopez_2019cohen_d + means_sd + means_se + means_ci + student_tNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
71 | 7 | el-Ebrahimi_2018 | el-Ebrahimi | 2018 | Everyday social skills | cohen_d + means_sd + student_t + variability_means_sd | g | cohen_d + means_sd + student_t | 3 | hierarchy | cohen_d | 0.669 | 0.081 | 0.51 | 0.829 | student_t | 0.617 | 0.081 | 0.457 | 0.776 | cohen_d | 0.669 | 0.081 | 0.51 | 0.829 | 0.053 | 0.715 | 0.028 | -- None available -- | 0 | hierarchy | 110 | Article | Strengths and Difficulties Questionnaire (SDQ) | 592 | 215 | 58.1 | 13.8 | 49.9 | 10.6 | 0.67 | 807 | 7.75 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | el-Ebrahimi_2018_cohen_d + means_sd + student_t + variability_means_sd_-- None available -- | cohen_d + means_sd + student_t | el-Ebrahimi_2018cohen_d + means_sd + student_tNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
81 | 8 | Ferguson_2021 | Ferguson | 2021 | Facial emotion recognition | cohen_d + means_sd + student_t + student_t_pval + variability_means_sd | g | cohen_d + means_sd + student_t + student_t_pval | 4 | hierarchy | cohen_d | 0.447 | 0.174 | 0.103 | 0.792 | means_sd | 0.442 | 0.174 | 0.097 | 0.786 | cohen_d | 0.447 | 0.174 | 0.103 | 0.792 | 0.006 | 0.983 | 0.003 | -- None available -- | 0 | hierarchy | 42 | Article | Faces test | 70 | 64 | 16.04 | 1.3 | 16.56 | 1.01 | 0.011 | 0.45 | 134 | -2.57 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | Ferguson_2021_cohen_d + means_sd + student_t + student_t_pval + variability_means_sd_-- None available -- | cohen_d + means_sd + student_t + student_t_pval | Ferguson_2021cohen_d + means_sd + student_t + student_t_pvalNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
91 | 9 | al-Ben_2017 | al-Ben | 2017 | Facial emotion recognition | etasq | g | etasq | 1 | hierarchy | etasq | 0.657 | 0.281 | 0.093 | 1.22 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | -- None available -- | 0 | hierarchy | 70 | Article | Facial emotion recognition | 26 | 26 | 0.1 | 52 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | al-Ben_2017_etasq_-- None available -- | etasq | al-Ben_2017etasqNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1 | 10 | Bohol_2014 | Bohol | 2014 | Facial emotion recognition | means_plot | g | means_plot | 1 | hierarchy | means_plot | 0.16 | 0.297 | -0.439 | 0.758 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_f | g | ancova_f | 1 | hierarchy | ancova_f | 0.078 | 0.282 | -0.492 | 0.649 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 12 | Article | Facial Expressions of Emotion: Stimuli and Tests (FEEST) | 22 | 22 | 2 | 0.3 | 0.077 | 44 | 6.775 | 7.1 | 7.025 | 7.355 | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Bohol_2014_means_plot_ancova_f | means_plot | ancova_f | Bohol_2014means_plotancova_f | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
111 | 11 | al-Ben_2017 | al-Ben | 2017 | Facial emotion recognition | means_plot | g | means_plot | 1 | hierarchy | means_plot | 0.814 | 0.285 | 0.242 | 1.385 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | -- None available -- | 0 | hierarchy | 70 | Article | Facial emotion recognition | 26 | 26 | 52 | 66.02 | 61.645 | 70.39 | 84.35 | 80.07 | 88.73 | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | al-Ben_2017_means_plot_-- None available -- | means_plot | al-Ben_2017means_plotNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
2 | 12 | Martinez_2001 | Martinez | 2001 | Everyday social skills | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 1.211 | 0.343 | 0.516 | 1.907 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_f | g | ancova_f | 1 | hierarchy | ancova_f | 0.76 | 0.312 | 0.126 | 1.393 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 39 | Article | Vineland Adaptative Behavior Scale - Socialization Domain | 21 | 18 | 77 | 14.1 | 94.1 | 13.5 | 2 | 0.3 | 6.42 | 39 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Martinez_2001_means_sd + variability_means_sd_ancova_f | means_sd | ancova_f | Martinez_2001means_sdancova_f | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
3 | 13 | Lopez_2019 | Lopez | 2019 | Facial emotion recognition | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 0.436 | 0.183 | 0.073 | 0.798 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_f + etasq_adj | g | ancova_f + etasq_adj | 2 | hierarchy | ancova_f | 0.345 | 0.174 | 0.001 | 0.689 | ancova_f | 0.345 | 0.174 | 0.001 | 0.689 | etasq_adj | 0.35 | 0.182 | -0.011 | 0.71 | 0.005 | 0.987 | 0.003 | 128 | Article | Facial emotion recognition | 52 | 72 | 3.52 | 2.58 | 2.61 | 1.62 | 0.03 | 2 | 0.3 | 2 | 0.3 | 4 | 124 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Lopez_2019_means_sd + variability_means_sd_ancova_f + etasq_adj | means_sd | ancova_f + etasq_adj | Lopez_2019means_sdancova_f + etasq_adj | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
4 | 14 | Yu_2018 | Yu | 2018 | Theory of mind | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 0.999 | 0.302 | 0.391 | 1.606 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_means_sd | g | ancova_means_sd | 1 | hierarchy | ancova_means_sd | 0.953 | 0.288 | 0.374 | 1.532 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 114 | Article | Reading the Mind in the Eyes Test (RMET) | 24 | 24 | 14.9 | 5.3 | 19.5 | 3.6 | 1 | 0.3 | 14.917 | 5.283 | 19.444 | 3.434 | 48 | TRUE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Yu_2018_means_sd + variability_means_sd_ancova_means_sd | means_sd | ancova_means_sd | Yu_2018means_sdancova_means_sd | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
5 | 15 | Mcgee_2019 | Mcgee | 2019 | Everyday social skills | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 0.896 | 0.203 | 0.493 | 1.3 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_means_se | g | ancova_means_se | 1 | hierarchy | ancova_means_se | 0.666 | 0.19 | 0.288 | 1.044 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 97 | Article | Social Communication Questionnaire (SCQ) | 46 | 61 | 4.83 | 3.32 | 2.3 | 2.34 | 1 | 0.3 | 4.85 | 0.53 | 2.26 | 0.48 | 107 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Mcgee_2019_means_sd + variability_means_sd_ancova_means_se | means_sd | ancova_means_se | Mcgee_2019means_sdancova_means_se | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
6 | 16 | Bayles_2013 | Bayles | 2013 | Everyday social skills | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 0.982 | 0.106 | 0.772 | 1.191 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | cohen_d_adj | g | cohen_d_adj | 1 | hierarchy | cohen_d_adj | 0.968 | 0.106 | 0.759 | 1.177 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 145 | Article | Social Adjustment Inventory for Children and Adolescents (SAICA) | 183 | 213 | 2.03 | 0.69 | 1.44 | 0.51 | 0.97 | 396 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Bayles_2013_means_sd + variability_means_sd_cohen_d_adj | means_sd | cohen_d_adj | Bayles_2013means_sdcohen_d_adj | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
7 | 17 | Dawkins_2016 | Dawkins | 2016 | Theory of mind | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 1.461 | 0.204 | 1.056 | 1.866 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | etasq_adj | g | etasq_adj | 1 | hierarchy | etasq_adj | 1.484 | 0.205 | 1.078 | 1.89 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 51 | Article | Reading the Mind in the Eyes Test (RMET) | 60 | 60 | 19.844 | 3.367 | 23.971 | 2.101 | 0.358 | 1 | 0.3 | 120 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Dawkins_2016_means_sd + variability_means_sd_etasq_adj | means_sd | etasq_adj | Dawkins_2016means_sdetasq_adj | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
181 | 18 | Caster_2011 | Caster | 2011 | Everyday social skills | means_sd + variability_means_sd | g | means_sd | 1 | hierarchy | means_sd | 1.225 | 0.285 | 0.654 | 1.795 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | -- None available -- | 0 | hierarchy | 15 | Thèse | Strengths and Difficulties Questionnaire (SDQ) | 35 | 24 | 4.31 | 2.69 | 1.47 | 1.51 | 59 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Caster_2011_means_sd + variability_means_sd_-- None available -- | means_sd | Caster_2011means_sdNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
19 | 19 | al-Abdullah_2013 | al-Abdullah | 2013 | Everyday social skills | means_sd + anova_f + variability_means_sd | g | means_sd + anova_f | 2 | hierarchy | means_sd | 1.601 | 0.288 | 1.025 | 2.177 | anova_f | 1.601 | 0.288 | 1.025 | 2.177 | means_sd | 1.601 | 0.288 | 1.025 | 2.177 | 0 | 1 | 0 | -- None available -- | 0 | hierarchy | 129 | Article | Social Skills Improvement System (SSIS) | 28 | 35 | 80.54 | 16.2 | 103.66 | 12.51 | 63 | 40.874 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | al-Abdullah_2013_means_sd + anova_f + variability_means_sd_-- None available -- | means_sd + anova_f | al-Abdullah_2013means_sd + anova_fNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
20 | 20 | Bushyhead_2017 | Bushyhead | 2017 | Empathy | means_sd + anova_f + etasq + variability_means_sd | g | means_sd + anova_f + etasq | 3 | hierarchy | means_sd | 0.116 | 0.177 | -0.235 | 0.467 | etasq | 0 | 0.177 | -0.351 | 0.351 | means_sd | 0.116 | 0.177 | -0.235 | 0.467 | 0.116 | 0.715 | 0.058 | -- None available -- | 0 | hierarchy | 64 | Article | Griffith Empathy Measure (GEM) | 65 | 61 | 41.54 | 9.69 | 42.61 | 8.5 | 0 | 126 | 0.135 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Bushyhead_2017_means_sd + anova_f + etasq + variability_means_sd_-- None available -- | means_sd + anova_f + etasq | Bushyhead_2017means_sd + anova_f + etasqNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
21 | 21 | el-Dib_2012 | el-Dib | 2012 | Everyday social skills | means_sd + anova_f + means_plot + variability_means_sd | g | means_sd + anova_f + means_plot | 3 | hierarchy | means_sd | 0.678 | 0.254 | 0.17 | 1.187 | means_plot | 0.561 | 0.252 | 0.057 | 1.064 | anova_f | 0.679 | 0.254 | 0.171 | 1.187 | 0.118 | 0.791 | 0.068 | -- None available -- | 0 | hierarchy | 16 | Thèse | Social Skills Rating System (SSRS) | 33 | 31 | 92.52 | 20.02 | 105.16 | 16.51 | 64 | 7.55 | 70.95 | 79.12 | 48.76 | 44.09 | 54.31 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | el-Dib_2012_means_sd + anova_f + means_plot + variability_means_sd_-- None available -- | means_sd + anova_f + means_plot | el-Dib_2012means_sd + anova_f + means_plotNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
22 | 22 | Steiner-Otoo_2020 | Steiner-Otoo | 2020 | Facial emotion recognition | means_sd + means_ci + student_t + variability_means_sd + variability_means_ci | g | means_sd + means_ci + student_t | 3 | hierarchy | means_sd | -0.178 | 0.269 | -0.718 | 0.362 | student_t | -0.188 | 0.269 | -0.728 | 0.352 | means_ci | -0.171 | 0.269 | -0.71 | 0.369 | 0.017 | 0.968 | 0.009 | -- None available -- | 0 | hierarchy | 32 | Article | Child Affective Facial Expression set (CAFE) | 28 | 26 | 2.5 | 1.2 | 2.3 | 1 | 2 | 3 | 1.9 | 2.7 | 54 | 0.7 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | Steiner-Otoo_2020_means_sd + means_ci + student_t + variability_means_sd + variability_means_ci_-- None available -- | means_sd + means_ci + student_t | Steiner-Otoo_2020means_sd + means_ci + student_tNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
23 | 23 | el-Dib_2012 | el-Dib | 2012 | Facial emotion recognition | means_sd + means_plot + variability_means_sd | g | means_sd + means_plot | 2 | hierarchy | means_sd | 0.774 | 0.251 | 0.274 | 1.275 | means_sd | 0.774 | 0.251 | 0.274 | 1.275 | means_plot | 0.785 | 0.251 | 0.284 | 1.286 | 0.01 | 0.98 | 0.007 | -- None available -- | 0 | hierarchy | 16 | Thèse | Facial emotion recognition | 33 | 34 | 2.24 | 1.46 | 1.18 | 1.24 | 67 | 2.24 | 1.985 | 2.495 | 1.175 | 0.96 | 1.375 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | el-Dib_2012_means_sd + means_plot + variability_means_sd_-- None available -- | means_sd + means_plot | el-Dib_2012means_sd + means_plotNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
8 | 24 | Womack_2013 | Womack | 2013 | Everyday social skills | means_sd + student_t + variability_means_sd | g | means_sd + student_t | 2 | hierarchy | means_sd | 1.373 | 0.192 | 0.993 | 1.753 | means_sd | 1.373 | 0.192 | 0.993 | 1.753 | student_t | 1.373 | 0.192 | 0.993 | 1.753 | 0 | 0.999 | 0 | ancova_f | g | ancova_f | 1 | hierarchy | ancova_f | 0.969 | 0.175 | 0.623 | 1.315 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 13 | Article | Child Behavior Checklist (CBCL) | 64 | 69 | 61.31 | 8.87 | 52.07 | 3.66 | 1 | 0.3 | 34.64 | 133 | 7.958 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Womack_2013_means_sd + student_t + variability_means_sd_ancova_f | means_sd + student_t | ancova_f | Womack_2013means_sd + student_tancova_f | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
25 | 25 | Cates_2000 | Cates | 2000 | Non-facial emotion recognition | means_sd + student_t + variability_means_sd | g | means_sd + student_t | 2 | hierarchy | means_sd | 0.776 | 0.239 | 0.3 | 1.252 | student_t | 0.729 | 0.238 | 0.255 | 1.203 | means_sd | 0.776 | 0.239 | 0.3 | 1.252 | 0.047 | 0.906 | 0.033 | -- None available -- | 0 | hierarchy | 43 | Article | Affective prosody | 37 | 37 | 0.84 | 0.17 | 0.94 | 0.06 | 74 | 3.17 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Cates_2000_means_sd + student_t + variability_means_sd_-- None available -- | means_sd + student_t | Cates_2000means_sd + student_tNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
9 | 26 | Mattice_2017 | Mattice | 2017 | Theory of mind | means_se + variability_means_se | g | means_se | 1 | hierarchy | means_se | 0.775 | 0.385 | -0.016 | 1.566 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_f + etasq_adj | g | ancova_f + etasq_adj | 2 | hierarchy | ancova_f | 0.697 | 0.365 | -0.056 | 1.449 | ancova_f | 0.697 | 0.365 | -0.056 | 1.449 | etasq_adj | 1.031 | 0.396 | 0.218 | 1.844 | 0.334 | 0.648 | 0.237 | 59 | Thèse | Flexibility and automaticy of social cognition (FASC) | 12 | 16 | 7.62 | 1.46 | 11.63 | 1.25 | 0.22 | 1 | 0.3 | 1 | 0.3 | 3.89 | 28 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Mattice_2017_means_se + variability_means_se_ancova_f + etasq_adj | means_se | ancova_f + etasq_adj | Mattice_2017means_seancova_f + etasq_adj | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
27 | 27 | al-Dallal_2013 | al-Dallal | 2013 | Everyday social skills | means_se + means_ci + variability_means_se + variability_means_ci | g | means_se + means_ci | 2 | hierarchy | means_se | 1.186 | 0.23 | 0.73 | 1.642 | means_ci | 1.183 | 0.229 | 0.727 | 1.639 | means_se | 1.186 | 0.23 | 0.73 | 1.642 | 0.003 | 0.994 | 0.002 | -- None available -- | 0 | hierarchy | 91 | Article | Pediatric Quality of Life Inventory (PEdsQL) | 45 | 43 | 69.92 | 3.9 | 93.72 | 1.47 | 62.05 | 77.8 | 90.73 | 96.7 | 88 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | al-Dallal_2013_means_se + means_ci + variability_means_se + variability_means_ci_-- None available -- | means_se + means_ci | al-Dallal_2013means_se + means_ciNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
10 | 28 | Yu_2018 | Yu | 2018 | Theory of mind | med_min_max | g | med_min_max | 1 | hierarchy | med_min_max | 2.709 | 0.396 | 1.911 | 3.507 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | ancova_means_sd | g | ancova_means_sd | 1 | hierarchy | ancova_means_sd | 1.439 | 0.308 | 0.819 | 2.06 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 114 | Article | False belief 1st order (smarties test / sally anne test) | 24 | 24 | 1 | 0.3 | 1.375 | 0.576 | 2 | 0 | 48 | 1 | 2 | 0 | 2 | 2 | 2 | FALSE | TRUE | FALSE | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Yu_2018_med_min_max_ancova_means_sd | med_min_max | ancova_means_sd | Yu_2018med_min_maxancova_means_sd | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
29 | 29 | Coppola_2012 | Coppola | 2012 | Everyday social skills | med_quarts | g | med_quarts | 1 | hierarchy | med_quarts | 2.208 | 0.174 | 1.866 | 2.55 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | -- None available -- | 0 | hierarchy | 38 | Poster | Social Responsiveness Scale (SRS) | 110 | 103 | 213 | 71.105 | 62.965 | 79 | 48.47 | 44.115 | 53.825 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Coppola_2012_med_quarts_-- None available -- | med_quarts | Coppola_2012med_quartsNA | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
11 | 30 | Mattice_2017 | Mattice | 2017 | Theory of mind | -- None available -- | 0 | hierarchy | ancova_f + etasq_adj | g | ancova_f + etasq_adj | 2 | hierarchy | ancova_f | 0.589 | 0.362 | -0.156 | 1.334 | ancova_f | 0.589 | 0.362 | -0.156 | 1.334 | etasq_adj | 0.879 | 0.389 | 0.079 | 1.678 | 0.29 | 0.684 | 0.205 | 59 | Thèse | Flexibility and automaticy of social cognition (FASC) | 12 | 16 | 0.17 | 1 | 0.3 | 1 | 0.3 | 2.78 | 28 | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Mattice_2017_-- None available --_ancova_f + etasq_adj | ancova_f + etasq_adj | Mattice_2017NAancova_f + etasq_adj | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
12 | 31 | Bushyhead_2017 | Bushyhead | 2017 | Facial emotion recognition | -- None available -- | 0 | hierarchy | ancova_means_plot | g | ancova_means_plot | 1 | hierarchy | ancova_means_plot | 0.481 | 0.172 | 0.141 | 0.821 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 64 | Article | The Diagnostic Analysis of Nonverbal Accuracy (DANVA) - face - adult / child | 65 | 61 | 1 | 0.3 | 126 | 0.99 | 1.88 | 0.595 | 1.235 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Bushyhead_2017_-- None available --_ancova_means_plot | ancova_means_plot | Bushyhead_2017NAancova_means_plot | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
13 | 32 | Colorado_2006 | Colorado | 2006 | Empathy | -- None available -- | 0 | hierarchy | ancova_means_sd | g | ancova_means_sd | 1 | hierarchy | ancova_means_sd | 0.474 | 0.344 | -0.232 | 1.18 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 133 | Thèse | Social Skills Rating System (SSRS) | 15 | 15 | 1 | 0.3 | 13.46 | 4.96 | 15.67 | 3.58 | 30 | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Colorado_2006_-- None available --_ancova_means_sd | ancova_means_sd | Colorado_2006NAancova_means_sd | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
14 | 33 | Smith_2012 | Smith | 2012 | Everyday social skills | -- None available -- | 0 | hierarchy | ancova_means_sd + ancova_f | g | ancova_means_sd + ancova_f | 2 | hierarchy | ancova_means_sd | 2.9 | 0.352 | 2.196 | 3.604 | ancova_f | 2.877 | 0.351 | 2.176 | 3.578 | ancova_means_sd | 2.9 | 0.352 | 2.196 | 3.604 | 0.023 | 0.968 | 0.016 | 10 | Article | Impairment rating scale (IRS) | 39 | 25 | 1 | 0.3 | 4.8 | 1.8 | 0.2 | 0.8 | 142.08 | 64 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Smith_2012_-- None available --_ancova_means_sd + ancova_f | ancova_means_sd + ancova_f | Smith_2012NAancova_means_sd + ancova_f | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
15 | 34 | al-Muhammed_2011 | al-Muhammed | 2011 | Theory of mind | -- None available -- | 0 | hierarchy | ancova_means_se | g | ancova_means_se | 1 | hierarchy | ancova_means_se | 0.774 | 0.312 | 0.14 | 1.408 | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | < 2 types of input data available | 89 | Thèse | Theory of Mind (NEPSY-II) | 18 | 21 | 2 | 0.3 | 100.19 | 2.62 | 108.74 | 2.09 | 39 | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | al-Muhammed_2011_-- None available --_ancova_means_se | ancova_means_se | al-Muhammed_2011NAancova_means_se | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
16 | 35 | Alexander_2021 | Alexander | 2021 | Everyday social skills | -- None available -- | 0 | hierarchy | ancova_means_se + ancova_means_ci | g | ancova_means_se + ancova_means_ci | 2 | hierarchy | ancova_means_se | 0.643 | 0.208 | 0.23 | 1.056 | ancova_means_se | 0.643 | 0.208 | 0.23 | 1.056 | ancova_means_ci | 0.659 | 0.208 | 0.246 | 1.073 | 0.017 | 0.96 | 0.012 | 3 | Article | Autism Quotient (C-AQ) | 33 | 64 | 2 | 0.3 | 11.2 | 0.86734693877551 | 7.79 | 0.630102040816326 | 9.5 | 12.9 | 6.55 | 9.02 | 97 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Alexander_2021_-- None available --_ancova_means_se + ancova_means_ci | ancova_means_se + ancova_means_ci | Alexander_2021NAancova_means_se + ancova_means_ci | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
17 | 36 | el-Azzi_2009 | el-Azzi | 2009 | Theory of mind | -- None available -- | 0 | hierarchy | cohen_d_adj + ancova_means_sd | g | cohen_d_adj + ancova_means_sd | 2 | hierarchy | cohen_d_adj | 0.415 | 0.267 | -0.12 | 0.951 | cohen_d_adj | 0.415 | 0.267 | -0.12 | 0.951 | ancova_means_sd | 0.489 | 0.256 | -0.025 | 1.003 | 0.074 | 0.869 | 0.052 | 146 | Article | adapté de Flavell / adapté Sally's anne task / adapté de smarties test | 26 | 30 | -0.421 | 1 | 0.3 | 3.23 | 1.18 | 3.77 | 0.9 | 56 | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | TRUE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | el-Azzi_2009_-- None available --_cohen_d_adj + ancova_means_sd | cohen_d_adj + ancova_means_sd | el-Azzi_2009NAcohen_d_adj + ancova_means_sd | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
18 | 37 | Gang_2010 | Gang | 2010 | Everyday social skills | -- None available -- | 0 | hierarchy | cohen_d_adj + ancova_means_sd + ancova_f | g | cohen_d_adj + ancova_means_sd + ancova_f | 3 | hierarchy | cohen_d_adj | 1.719 | 0.35 | 1.014 | 2.424 | ancova_f | 1.456 | 0.324 | 0.803 | 2.11 | cohen_d_adj | 1.719 | 0.35 | 1.014 | 2.424 | 0.263 | 0.676 | 0.134 | 124 | Article | Impairment rating scale (IRS) | 27 | 18 | 1.75 | 1 | 0.3 | 3.48 | 1.7 | 0.67 | 1.46 | 26.1 | 45 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | Gang_2010_-- None available --_cohen_d_adj + ancova_means_sd + ancova_f | cohen_d_adj + ancova_means_sd + ancova_f | Gang_2010NAcohen_d_adj + ancova_means_sd + ancova_f | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | 0.5 | 0.5 | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | FALSE | raw_scale | FALSE | metaumbrella | metaumbrella_cases | bonett | viechtbauer | bonett | viechtbauer |
To know more about the information stored in each column, refer to documentation of the summary.metaConvert function, available in the R manual of this package.
A tutorial on a more advanced usage will be proposed in the companion paper of this tool; the link will be inserted as soon as the paper will be published.
For now, you can refer to the documentation of the convert_df function in the R manual of this package, in which all options are described.
If you prefer having a graphical user interface (GUI) when performing data analysis, we are please to introduce you to our web-app that enables to perform ALL calculations of this package using an interactive GUI https://metaconvert.org/