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 |
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