Last updated on 2025-01-17 10:48:29 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.9-0 | 35.24 | 407.28 | 442.52 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 2.9-0 | 20.91 | 253.85 | 274.76 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 2.9-0 | 748.51 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 2.9-0 | 533.10 | ERROR | |||
| r-devel-windows-x86_64 | 2.9-0 | 35.00 | 520.00 | 555.00 | NOTE | |
| r-patched-linux-x86_64 | 2.9-0 | 40.45 | 458.58 | 499.03 | OK | |
| r-release-linux-x86_64 | 2.9-0 | 30.52 | 385.64 | 416.16 | ERROR | |
| r-release-macos-arm64 | 2.9-0 | 191.00 | OK | |||
| r-release-macos-x86_64 | 2.9-0 | 311.00 | OK | |||
| r-release-windows-x86_64 | 2.9-0 | 33.00 | 514.00 | 547.00 | 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 | 676.00 | 718.00 | 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 9.857 0.102 12.096
Dong2013 7.715 0.058 9.291
netmetabin 7.630 0.012 9.536
netpairwise 7.277 0.024 8.923
netmeasures 7.072 0.020 9.335
forest.netmeta 6.714 0.012 8.476
as.data.frame.netmeta 6.406 0.079 8.475
netmatrix 6.433 0.016 8.624
netmeta 6.394 0.020 9.612
netgraph 6.364 0.008 8.808
invmat 6.355 0.012 7.725
netgraph.netmeta 6.262 0.016 7.451
netdistance 6.246 0.016 7.757
netbind 6.088 0.008 8.618
forest.netcomparison 5.948 0.000 8.424
forest.netbind 5.834 0.016 8.125
netcomb 5.720 0.020 7.174
forest.netcomplex 5.720 0.008 7.082
Franchini2012 5.356 0.075 6.833
netimpact 5.329 0.008 7.326
netgraph.netimpact 5.255 0.047 7.024
netcontrib 5.149 0.008 7.748
forest.netcomb 5.084 0.009 6.824
dietaryfat 4.769 0.027 5.824
netgraph.netcomb 4.751 0.012 5.811
netcomparison 4.702 0.004 5.968
netcomplex 4.675 0.012 6.427
Linde2016 4.640 0.012 5.977
netheat 4.599 0.020 5.580
forest.netsplit 4.128 0.016 5.519
netleague 4.084 0.007 5.205
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 5.738 0.235 7.152
Dong2013 4.444 0.072 5.654
netmetabin 4.409 0.034 5.345
netpairwise 4.148 0.052 5.218
netmeasures 4.034 0.071 5.113
Franchini2012 3.455 0.087 6.342
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 2.9-0
Check: Rd cross-references
Result: NOTE
Undeclared package ‘crossnma’ in Rd xrefs
Unknown package ‘hasseDiagram’ in Rd xrefs
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 2.9-0
Check: examples
Result: ERROR
Running examples in ‘netmeta-Ex.R’ failed
The error most likely occurred in:
> ### 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-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 2.9-0
Check: Rd cross-references
Result: NOTE
Unknown package ‘hasseDiagram’ in Rd xrefs
Flavors: r-devel-linux-x86_64-fedora-gcc, r-release-linux-x86_64
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’
Flavor: 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
Flavor: r-release-linux-x86_64