CRAN Package Check Results for Package netmeta

Last updated on 2025-01-22 14:52:44 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.9-0 34.39 413.20 447.59 ERROR
r-devel-linux-x86_64-debian-gcc 2.9-0 21.29 257.83 279.12 ERROR
r-devel-linux-x86_64-fedora-clang 3.0-2 959.01 OK
r-devel-linux-x86_64-fedora-gcc 3.0-2 918.92 OK
r-devel-windows-x86_64 2.9-0 29.00 503.00 532.00 NOTE
r-patched-linux-x86_64 2.9-0 40.39 383.09 423.48 ERROR
r-release-linux-x86_64 2.9-0 27.97 383.90 411.87 ERROR
r-release-macos-arm64 2.9-0 191.00 OK
r-release-macos-x86_64 3.0-2 492.00 OK
r-release-windows-x86_64 2.9-0 30.00 505.00 535.00 OK
r-oldrel-macos-arm64 2.9-0 159.00 OK
r-oldrel-macos-x86_64 2.9-0 353.00 OK
r-oldrel-windows-x86_64 2.9-0 42.00 673.00 715.00 OK

Additional issues

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Check Details

Version: 2.9-0
Check: Rd cross-references
Result: NOTE Found the following Rd file(s) with Rd \link{} targets missing package anchors: Baker2009.Rd: metabin Dogliotti2014.Rd: metabin Dong2013.Rd: metabin Franchini2012.Rd: metacont Gurusamy2011.Rd: metabin Linde2015.Rd: metabin Stowe2010.Rd: metacont Woods2010.Rd: metabin dietaryfat.Rd: metainc forest.netbind.Rd: forest.meta forest.netcomb.Rd: forest.meta forest.netcomparison.Rd: forest.meta forest.netcomplex.Rd: forest.meta forest.netmeta.Rd: forest.meta forest.netsplit.Rd: forest.meta funnel.netmeta.Rd: funnel.meta, metabias metabias.netmeta.Rd: metabias netmeta.Rd: metabin, metacont, metainc, metagen netpairwise.Rd: metagen pairwise.Rd: metabin, metacont, metainc, metagen radial.netmeta.Rd: radial.meta, funnel.meta, metabias smokingcessation.Rd: metabin Please provide package anchors for all Rd \link{} targets not in the package itself and the base packages. Unknown package ‘hasseDiagram’ in Rd xrefs Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc

Version: 2.9-0
Check: examples
Result: ERROR Running examples in ‘netmeta-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: netposet > ### Title: Partial order of treatments in network meta-analysis > ### Aliases: netposet print.netposet > > ### ** Examples > > ## Not run: > ##D # Use depression dataset > ##D # > ##D data(Linde2015) > ##D > ##D # Define order of treatments > ##D # > ##D trts <- c("TCA", "SSRI", "SNRI", "NRI", > ##D "Low-dose SARI", "NaSSa", "rMAO-A", "Hypericum", "Placebo") > ##D > ##D # Outcome labels > ##D # > ##D outcomes <- c("Early response", "Early remission") > ##D > ##D # (1) Early response > ##D # > ##D p1 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(resp1, resp2, resp3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net1 <- netmeta(p1, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "undesirable") > ##D > ##D # (2) Early remission > ##D # > ##D p2 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(remi1, remi2, remi3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net2 <- netmeta(p2, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "undesirable") > ##D > ##D # Partial order of treatment rankings (two outcomes) > ##D # > ##D po <- netposet(netrank(net1), netrank(net2), outcomes = outcomes) > ##D > ##D # Hasse diagram > ##D # > ##D hasse(po) > ##D > ##D > ##D # > ##D # Outcome labels > ##D # > ##D outcomes <- c("Early response", "Early remission", > ##D "Lost to follow-up", "Lost to follow-up due to AEs", > ##D "Adverse events (AEs)") > ##D > ##D # (3) Loss to follow-up > ##D # > ##D p3 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(loss1, loss2, loss3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net3 <- netmeta(p3, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # (4) Loss to follow-up due to adverse events > ##D # > ##D p4 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(loss.ae1, loss.ae2, loss.ae3), n = list(n1, n2, n3), > ##D studlab = id, data = subset(Linde2015, id != 55), sm = "OR") > ##D # > ##D net4 <- netmeta(p4, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # (5) Adverse events > ##D # > ##D p5 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(ae1, ae2, ae3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net5 <- netmeta(p5, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # Partial order of treatment rankings (all five outcomes) > ##D # > ##D po.ranks <- netposet(netrank(net1), netrank(net2), > ##D netrank(net3), netrank(net4), netrank(net5), outcomes = outcomes) > ##D > ##D # Same result > ##D # > ##D po.nets <- netposet(net1, net2, net3, net4, net5, > ##D outcomes = outcomes) > ##D # > ##D all.equal(po.ranks, po.nets) > ##D > ##D # Print matrix with P-scores (random effects model) > ##D # > ##D po.nets$P.random > ##D > ##D # Hasse diagram for all outcomes (random effects model) > ##D # > ##D hasse(po.ranks) > ##D > ##D # Hasse diagram for outcomes early response and early remission > ##D # > ##D po12 <- netposet(netrank(net1), netrank(net2), > ##D outcomes = outcomes[1:2]) > ##D hasse(po12) > ##D > ##D # Scatter plot > ##D # > ##D oldpar <- par(pty = "s") > ##D plot(po12) > ##D par(oldpar) > ## End(Not run) > > # Example using ranking matrix with P-scores > # > # Ribassin-Majed L, Marguet S, Lee A.W., et al. (2017): > # What is the best treatment of locally advanced nasopharyngeal > # carcinoma? An individual patient data network meta-analysis. > # Journal of Clinical Oncology, 35, 498-505 > # > outcomes <- c("OS", "PFS", "LC", "DC") > treatments <- c("RT", "IC-RT", "IC-CRT", "CRT", + "CRT-AC", "RT-AC", "IC-RT-AC") > # > # P-scores (from Table 1) > # > pscore.os <- c(15, 33, 63, 70, 96, 28, 45) / 100 > pscore.pfs <- c( 4, 46, 79, 52, 94, 36, 39) / 100 > pscore.lc <- c( 9, 27, 47, 37, 82, 58, 90) / 100 > pscore.dc <- c(16, 76, 95, 48, 72, 32, 10) / 100 > # > pscore.matrix <- data.frame(pscore.os, pscore.pfs, pscore.lc, pscore.dc) > rownames(pscore.matrix) <- treatments > colnames(pscore.matrix) <- outcomes > pscore.matrix OS PFS LC DC RT 0.15 0.04 0.09 0.16 IC-RT 0.33 0.46 0.27 0.76 IC-CRT 0.63 0.79 0.47 0.95 CRT 0.70 0.52 0.37 0.48 CRT-AC 0.96 0.94 0.82 0.72 RT-AC 0.28 0.36 0.58 0.32 IC-RT-AC 0.45 0.39 0.90 0.10 > # > po <- netposet(pscore.matrix) > po12 <- netposet(pscore.matrix[, 1:2]) > po RT IC-RT IC-CRT CRT CRT-AC RT-AC IC-RT-AC RT 0 0 0 0 0 0 0 IC-RT 1 0 0 0 0 0 0 IC-CRT 0 1 0 0 0 0 0 CRT 1 0 0 0 0 0 0 CRT-AC 0 0 0 1 0 1 0 RT-AC 1 0 0 0 0 0 0 IC-RT-AC 0 0 0 0 0 0 0 > po12 RT IC-RT IC-CRT CRT CRT-AC RT-AC IC-RT-AC RT 0 0 0 0 0 0 0 IC-RT 0 0 0 0 0 1 0 IC-CRT 0 1 0 0 0 0 1 CRT 0 1 0 0 0 0 1 CRT-AC 0 0 1 1 0 0 0 RT-AC 1 0 0 0 0 0 0 IC-RT-AC 0 0 0 0 0 1 0 > # > hasse(po) Error: Package 'hasseDiagram' missing. Please use the following R commands for installation: install.packages("BiocManager") BiocManager::install() BiocManager::install("Rgraphviz") install.packages("hasseDiagram") Execution halted Examples with CPU (user + system) or elapsed time > 5s user system elapsed Gurusamy2011 9.945 0.155 12.540 Dong2013 8.105 0.149 10.190 netmetabin 7.804 0.016 9.714 netpairwise 7.283 0.024 8.792 netmeasures 7.226 0.016 10.060 forest.netmeta 6.956 0.018 10.150 netgraph.netmeta 6.508 0.012 8.289 invmat 6.447 0.012 8.389 netdistance 6.375 0.051 9.266 netmatrix 6.418 0.008 8.222 netmeta 6.406 0.020 8.526 netgraph 6.408 0.017 9.849 as.data.frame.netmeta 6.256 0.031 7.903 netbind 6.092 0.008 8.844 forest.netbind 5.958 0.008 8.136 forest.netcomparison 5.875 0.016 8.181 forest.netcomplex 5.841 0.016 7.698 netcomb 5.656 0.012 7.247 Franchini2012 5.532 0.096 7.408 netcontrib 5.419 0.036 6.212 netimpact 5.313 0.011 7.150 netgraph.netimpact 5.179 0.004 6.562 forest.netcomb 5.169 0.007 7.226 netcomplex 5.017 0.000 7.688 netcomparison 4.975 0.020 7.081 netgraph.netcomb 4.857 0.032 6.907 dietaryfat 4.851 0.001 5.297 Linde2016 4.641 0.004 5.076 netheat 4.520 0.028 5.400 decomp.design 4.234 0.008 5.728 Stowe2010 4.091 0.042 5.564 forest.netsplit 4.110 0.008 5.697 netleague 4.102 0.008 5.106 heatplot 3.654 0.012 5.443 heatplot.netmeta 3.536 0.004 5.053 Flavor: r-devel-linux-x86_64-debian-clang

Version: 2.9-0
Check: examples
Result: ERROR Running examples in ‘netmeta-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: netposet > ### Title: Partial order of treatments in network meta-analysis > ### Aliases: netposet print.netposet > > ### ** Examples > > ## Not run: > ##D # Use depression dataset > ##D # > ##D data(Linde2015) > ##D > ##D # Define order of treatments > ##D # > ##D trts <- c("TCA", "SSRI", "SNRI", "NRI", > ##D "Low-dose SARI", "NaSSa", "rMAO-A", "Hypericum", "Placebo") > ##D > ##D # Outcome labels > ##D # > ##D outcomes <- c("Early response", "Early remission") > ##D > ##D # (1) Early response > ##D # > ##D p1 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(resp1, resp2, resp3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net1 <- netmeta(p1, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "undesirable") > ##D > ##D # (2) Early remission > ##D # > ##D p2 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(remi1, remi2, remi3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net2 <- netmeta(p2, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "undesirable") > ##D > ##D # Partial order of treatment rankings (two outcomes) > ##D # > ##D po <- netposet(netrank(net1), netrank(net2), outcomes = outcomes) > ##D > ##D # Hasse diagram > ##D # > ##D hasse(po) > ##D > ##D > ##D # > ##D # Outcome labels > ##D # > ##D outcomes <- c("Early response", "Early remission", > ##D "Lost to follow-up", "Lost to follow-up due to AEs", > ##D "Adverse events (AEs)") > ##D > ##D # (3) Loss to follow-up > ##D # > ##D p3 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(loss1, loss2, loss3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net3 <- netmeta(p3, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # (4) Loss to follow-up due to adverse events > ##D # > ##D p4 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(loss.ae1, loss.ae2, loss.ae3), n = list(n1, n2, n3), > ##D studlab = id, data = subset(Linde2015, id != 55), sm = "OR") > ##D # > ##D net4 <- netmeta(p4, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # (5) Adverse events > ##D # > ##D p5 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(ae1, ae2, ae3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net5 <- netmeta(p5, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # Partial order of treatment rankings (all five outcomes) > ##D # > ##D po.ranks <- netposet(netrank(net1), netrank(net2), > ##D netrank(net3), netrank(net4), netrank(net5), outcomes = outcomes) > ##D > ##D # Same result > ##D # > ##D po.nets <- netposet(net1, net2, net3, net4, net5, > ##D outcomes = outcomes) > ##D # > ##D all.equal(po.ranks, po.nets) > ##D > ##D # Print matrix with P-scores (random effects model) > ##D # > ##D po.nets$P.random > ##D > ##D # Hasse diagram for all outcomes (random effects model) > ##D # > ##D hasse(po.ranks) > ##D > ##D # Hasse diagram for outcomes early response and early remission > ##D # > ##D po12 <- netposet(netrank(net1), netrank(net2), > ##D outcomes = outcomes[1:2]) > ##D hasse(po12) > ##D > ##D # Scatter plot > ##D # > ##D oldpar <- par(pty = "s") > ##D plot(po12) > ##D par(oldpar) > ## End(Not run) > > # Example using ranking matrix with P-scores > # > # Ribassin-Majed L, Marguet S, Lee A.W., et al. (2017): > # What is the best treatment of locally advanced nasopharyngeal > # carcinoma? An individual patient data network meta-analysis. > # Journal of Clinical Oncology, 35, 498-505 > # > outcomes <- c("OS", "PFS", "LC", "DC") > treatments <- c("RT", "IC-RT", "IC-CRT", "CRT", + "CRT-AC", "RT-AC", "IC-RT-AC") > # > # P-scores (from Table 1) > # > pscore.os <- c(15, 33, 63, 70, 96, 28, 45) / 100 > pscore.pfs <- c( 4, 46, 79, 52, 94, 36, 39) / 100 > pscore.lc <- c( 9, 27, 47, 37, 82, 58, 90) / 100 > pscore.dc <- c(16, 76, 95, 48, 72, 32, 10) / 100 > # > pscore.matrix <- data.frame(pscore.os, pscore.pfs, pscore.lc, pscore.dc) > rownames(pscore.matrix) <- treatments > colnames(pscore.matrix) <- outcomes > pscore.matrix OS PFS LC DC RT 0.15 0.04 0.09 0.16 IC-RT 0.33 0.46 0.27 0.76 IC-CRT 0.63 0.79 0.47 0.95 CRT 0.70 0.52 0.37 0.48 CRT-AC 0.96 0.94 0.82 0.72 RT-AC 0.28 0.36 0.58 0.32 IC-RT-AC 0.45 0.39 0.90 0.10 > # > po <- netposet(pscore.matrix) > po12 <- netposet(pscore.matrix[, 1:2]) > po RT IC-RT IC-CRT CRT CRT-AC RT-AC IC-RT-AC RT 0 0 0 0 0 0 0 IC-RT 1 0 0 0 0 0 0 IC-CRT 0 1 0 0 0 0 0 CRT 1 0 0 0 0 0 0 CRT-AC 0 0 0 1 0 1 0 RT-AC 1 0 0 0 0 0 0 IC-RT-AC 0 0 0 0 0 0 0 > po12 RT IC-RT IC-CRT CRT CRT-AC RT-AC IC-RT-AC RT 0 0 0 0 0 0 0 IC-RT 0 0 0 0 0 1 0 IC-CRT 0 1 0 0 0 0 1 CRT 0 1 0 0 0 0 1 CRT-AC 0 0 1 1 0 0 0 RT-AC 1 0 0 0 0 0 0 IC-RT-AC 0 0 0 0 0 1 0 > # > hasse(po) Error: Package 'hasseDiagram' missing. Please use the following R commands for installation: install.packages("BiocManager") BiocManager::install() BiocManager::install("Rgraphviz") install.packages("hasseDiagram") Execution halted Examples with CPU (user + system) or elapsed time > 5s user system elapsed Gurusamy2011 5.926 0.224 6.685 Dong2013 4.631 0.082 5.260 netmetabin 4.651 0.043 6.011 netpairwise 4.412 0.027 6.194 netmeasures 4.293 0.087 5.398 forest.netmeta 4.083 0.015 5.312 netgraph.netmeta 4.006 0.059 5.806 invmat 3.949 0.012 5.280 netgraph 3.849 0.074 5.523 netmeta 3.810 0.016 5.351 netmatrix 3.776 0.007 5.155 Flavor: r-devel-linux-x86_64-debian-gcc

Version: 2.9-0
Check: Rd cross-references
Result: NOTE Found the following Rd file(s) with Rd \link{} targets missing package anchors: Baker2009.Rd: metabin Dogliotti2014.Rd: metabin Dong2013.Rd: metabin Franchini2012.Rd: metacont Gurusamy2011.Rd: metabin Linde2015.Rd: metabin Stowe2010.Rd: metacont Woods2010.Rd: metabin dietaryfat.Rd: metainc forest.netbind.Rd: forest.meta forest.netcomb.Rd: forest.meta forest.netcomparison.Rd: forest.meta forest.netcomplex.Rd: forest.meta forest.netmeta.Rd: forest.meta forest.netsplit.Rd: forest.meta funnel.netmeta.Rd: funnel.meta, metabias metabias.netmeta.Rd: metabias netmeta.Rd: metabin, metacont, metainc, metagen netpairwise.Rd: metagen pairwise.Rd: metabin, metacont, metainc, metagen radial.netmeta.Rd: radial.meta, funnel.meta, metabias smokingcessation.Rd: metabin Please provide package anchors for all Rd \link{} targets not in the package itself and the base packages. Flavor: r-devel-windows-x86_64

Version: 2.9-0
Check: package dependencies
Result: NOTE Package suggested but not available for checking: ‘hasseDiagram’ Flavors: r-patched-linux-x86_64, r-release-linux-x86_64

Version: 2.9-0
Check: Rd cross-references
Result: NOTE Unknown package ‘hasseDiagram’ in Rd xrefs Flavors: r-patched-linux-x86_64, r-release-linux-x86_64

Version: 2.9-0
Check: examples
Result: ERROR Running examples in ‘netmeta-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: netposet > ### Title: Partial order of treatments in network meta-analysis > ### Aliases: netposet print.netposet > > ### ** Examples > > ## Not run: > ##D # Use depression dataset > ##D # > ##D data(Linde2015) > ##D > ##D # Define order of treatments > ##D # > ##D trts <- c("TCA", "SSRI", "SNRI", "NRI", > ##D "Low-dose SARI", "NaSSa", "rMAO-A", "Hypericum", "Placebo") > ##D > ##D # Outcome labels > ##D # > ##D outcomes <- c("Early response", "Early remission") > ##D > ##D # (1) Early response > ##D # > ##D p1 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(resp1, resp2, resp3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net1 <- netmeta(p1, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "undesirable") > ##D > ##D # (2) Early remission > ##D # > ##D p2 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(remi1, remi2, remi3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net2 <- netmeta(p2, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "undesirable") > ##D > ##D # Partial order of treatment rankings (two outcomes) > ##D # > ##D po <- netposet(netrank(net1), netrank(net2), outcomes = outcomes) > ##D > ##D # Hasse diagram > ##D # > ##D hasse(po) > ##D > ##D > ##D # > ##D # Outcome labels > ##D # > ##D outcomes <- c("Early response", "Early remission", > ##D "Lost to follow-up", "Lost to follow-up due to AEs", > ##D "Adverse events (AEs)") > ##D > ##D # (3) Loss to follow-up > ##D # > ##D p3 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(loss1, loss2, loss3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net3 <- netmeta(p3, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # (4) Loss to follow-up due to adverse events > ##D # > ##D p4 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(loss.ae1, loss.ae2, loss.ae3), n = list(n1, n2, n3), > ##D studlab = id, data = subset(Linde2015, id != 55), sm = "OR") > ##D # > ##D net4 <- netmeta(p4, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # (5) Adverse events > ##D # > ##D p5 <- pairwise(treat = list(treatment1, treatment2, treatment3), > ##D event = list(ae1, ae2, ae3), n = list(n1, n2, n3), > ##D studlab = id, data = Linde2015, sm = "OR") > ##D # > ##D net5 <- netmeta(p5, common = FALSE, > ##D seq = trts, ref = "Placebo", small.values = "desirable") > ##D > ##D # Partial order of treatment rankings (all five outcomes) > ##D # > ##D po.ranks <- netposet(netrank(net1), netrank(net2), > ##D netrank(net3), netrank(net4), netrank(net5), outcomes = outcomes) > ##D > ##D # Same result > ##D # > ##D po.nets <- netposet(net1, net2, net3, net4, net5, > ##D outcomes = outcomes) > ##D # > ##D all.equal(po.ranks, po.nets) > ##D > ##D # Print matrix with P-scores (random effects model) > ##D # > ##D po.nets$P.random > ##D > ##D # Hasse diagram for all outcomes (random effects model) > ##D # > ##D hasse(po.ranks) > ##D > ##D # Hasse diagram for outcomes early response and early remission > ##D # > ##D po12 <- netposet(netrank(net1), netrank(net2), > ##D outcomes = outcomes[1:2]) > ##D hasse(po12) > ##D > ##D # Scatter plot > ##D # > ##D oldpar <- par(pty = "s") > ##D plot(po12) > ##D par(oldpar) > ## End(Not run) > > # Example using ranking matrix with P-scores > # > # Ribassin-Majed L, Marguet S, Lee A.W., et al. (2017): > # What is the best treatment of locally advanced nasopharyngeal > # carcinoma? An individual patient data network meta-analysis. > # Journal of Clinical Oncology, 35, 498-505 > # > outcomes <- c("OS", "PFS", "LC", "DC") > treatments <- c("RT", "IC-RT", "IC-CRT", "CRT", + "CRT-AC", "RT-AC", "IC-RT-AC") > # > # P-scores (from Table 1) > # > pscore.os <- c(15, 33, 63, 70, 96, 28, 45) / 100 > pscore.pfs <- c( 4, 46, 79, 52, 94, 36, 39) / 100 > pscore.lc <- c( 9, 27, 47, 37, 82, 58, 90) / 100 > pscore.dc <- c(16, 76, 95, 48, 72, 32, 10) / 100 > # > pscore.matrix <- data.frame(pscore.os, pscore.pfs, pscore.lc, pscore.dc) > rownames(pscore.matrix) <- treatments > colnames(pscore.matrix) <- outcomes > pscore.matrix OS PFS LC DC RT 0.15 0.04 0.09 0.16 IC-RT 0.33 0.46 0.27 0.76 IC-CRT 0.63 0.79 0.47 0.95 CRT 0.70 0.52 0.37 0.48 CRT-AC 0.96 0.94 0.82 0.72 RT-AC 0.28 0.36 0.58 0.32 IC-RT-AC 0.45 0.39 0.90 0.10 > # > po <- netposet(pscore.matrix) > po12 <- netposet(pscore.matrix[, 1:2]) > po RT IC-RT IC-CRT CRT CRT-AC RT-AC IC-RT-AC RT 0 0 0 0 0 0 0 IC-RT 1 0 0 0 0 0 0 IC-CRT 0 1 0 0 0 0 0 CRT 1 0 0 0 0 0 0 CRT-AC 0 0 0 1 0 1 0 RT-AC 1 0 0 0 0 0 0 IC-RT-AC 0 0 0 0 0 0 0 > po12 RT IC-RT IC-CRT CRT CRT-AC RT-AC IC-RT-AC RT 0 0 0 0 0 0 0 IC-RT 0 0 0 0 0 1 0 IC-CRT 0 1 0 0 0 0 1 CRT 0 1 0 0 0 0 1 CRT-AC 0 0 1 1 0 0 0 RT-AC 1 0 0 0 0 0 0 IC-RT-AC 0 0 0 0 0 1 0 > # > hasse(po) Error: Package 'hasseDiagram' missing. Please use the following R commands for installation: install.packages("BiocManager") BiocManager::install() BiocManager::install("Rgraphviz") install.packages("hasseDiagram") Execution halted Flavors: r-patched-linux-x86_64, r-release-linux-x86_64