Dear Rich,
w/o the original data we can actually only guess, but I think you
may haven't been patient enough to let summary.glht finish its
job. Have you tried to increase the number of contrasts, i.e.
comparisons, step by step to see how the computational burden and
hence the required computing time increases?
Internally, a lot effort goes into the computation of probabilities
and/or quantiles of multivariate normal or t distributions, and in
your setting they *are* high-dimensional. For more reliable and
elaborate details you may have to consult the cited references in
?summary.glht, or wait/hope for a more knowledgeable list member to
"jump in".
Hth -- Gerrit
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Am 08.11.2018 um 18:10 schrieb Friedman, Richard A.:
Dear List.
I ran multcomp with 27 comaprisons. The glht command returned an mcp object,
but the summary command with the Westfall correction ddi not give a summary.
When I ran the same dataset with 4 comparisons I got p-values. When I sued a
summary with
univariate or Bonferroni’s method with all 27 comarisons I got p-values. But
all 27 did not
work for Wesrfall. Please advise.
Here is a record of my session with 27 comparisons and Westfall:
R version 3.5.1 (2018-07-02) -- "Feather Spray"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin15.6.0 (64-bit)
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[R.app GUI 1.70 (7543) x86_64-apple-darwin15.6.0]
[History restored from /Users/friedman/.Rapp.history]
objc[31790]: Class FIFinderSyncExtensionHost is implemented in both
/System/Library/PrivateFrameworks/FinderKit.framework/Versions/A/FinderKit
(0x7fff9c2b7c90) and
/System/Library/PrivateFrameworks/FileProvider.framework/OverrideBundles/FinderSyncCollaborationFileProviderOverride.bundle/Contents/MacOS/FinderSyncCollaborationFileProviderOverride
(0x119bf8cd8). One of the two will be used. Which one is undefined.
library(multcomp)
Loading required package: mvtnorm
Loading required package: survival
Loading required package: TH.data
Loading required package: MASS
Attaching package: ‘TH.data’
The following object is masked from ‘package:MASS’:
geyser
tumor<-read.table("a8_1wayall_input.txt",sep="\t",header=T)
class(tumor)
[1] "data.frame"
dim(tumor)
[1] 309 2
tumor[1,]
condition log2vol
1 aa.vector.4w 7.297375
model<-lm(log2vol~condition,data=tumor)
summary(model)
Call:
lm(formula = log2vol ~ condition, data = tumor)
Residuals:
Min 1Q Median 3Q Max
-7.997 -2.414 0.291 2.164 8.059
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.58776 0.60457 7.588 4.3e-13 ***
conditionab.vector.6w 1.39818 0.85499 1.635 0.103054
conditionac.vector.8w 2.89085 0.85499 3.381 0.000820 ***
conditionba.dnmt1kd.4w -2.67491 0.84733 -3.157 0.001760 **
conditionbb.dnmt1kd.6w -1.43390 0.84733 -1.692 0.091654 .
conditionbc.dnmt1kd.8w -0.47188 0.84733 -0.557 0.578020
conditionca.dnmt3bkd.4w -3.15325 0.89139 -3.537 0.000469 ***
conditioncb.dnmt3bkd.6w -2.17334 0.89139 -2.438 0.015355 *
conditioncc.dnmt3bkd.8w -1.50187 0.89139 -1.685 0.093078 .
conditionda.dnmt1kdhrad9.4w 1.08153 1.08991 0.992 0.321863
conditiondb.dnmt1kdhrad9.6w 2.38383 1.08991 2.187 0.029517 *
conditiondc.dnmt1kdhrad9.8w 3.53990 1.08991 3.248 0.001297 **
conditionea.dnmt3bkdhrad9.4w 0.02795 1.06049 0.026 0.978991
conditioneb.dnmt3bkdhrad9.6w 1.34037 1.06049 1.264 0.207263
conditionec.dnmt3bkdhrad9.8w 3.40955 1.06049 3.215 0.001449 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 3.141 on 294 degrees of freedom
Multiple R-squared: 0.3155, Adjusted R-squared: 0.2829
F-statistic: 9.678 on 14 and 294 DF, p-value: < 2.2e-16
model.mc<-glht(model,linfct=mcp(condition=c("ab.vector.6w-aa.vector.4w=0",
+ "ac.vector.8w-aa.vector.4w=0",
+ "ac.vector.8w-ab.vector.6w=0",
+ "bb.dnmt1kd.6w-ba.dnmt1kd.4w=0",
+ "bc.dnmt1kd.8w-ba.dnmt1kd.4w=0",
+ "bc.dnmt1kd.8w-bb.dnmt1kd.6w=0",
+ "cb.dnmt3bkd.6w-ca.dnmt3bkd.4w=0",
+ "cc.dnmt3bkd.8w-ca.dnmt3bkd.4w=0",
+ "cc.dnmt3bkd.8w-cb.dnmt3bkd.6w=0",
+ "db.dnmt1kdhrad9.6w-da.dnmt1kdhrad9.4w=0",
+ "dc.dnmt1kdhrad9.8w-da.dnmt1kdhrad9.4w=0",
+ "dc.dnmt1kdhrad9.8w-db.dnmt1kdhrad9.6w=0",
+ "eb.dnmt3bkdhrad9.6w-ea.dnmt3bkdhrad9.4w=0",
+ "ec.dnmt3bkdhrad9.8w-ea.dnmt3bkdhrad9.4w=0",
+ "ec.dnmt3bkdhrad9.8w-eb.dnmt3bkdhrad9.6w=0",
+ "ba.dnmt1kd.4w-aa.vector.4w=0",
+ "ca.dnmt3bkd.4w-aa.vector.4w=0",
+ "da.dnmt1kdhrad9.4w-ba.dnmt1kd.4w=0",
+ "ea.dnmt3bkdhrad9.4w-ca.dnmt3bkd.4w=0",
+ "bb.dnmt1kd.6w-ab.vector.6w=0",
+ "cb.dnmt3bkd.6w-ab.vector.6w=0",
+ "db.dnmt1kdhrad9.6w-bb.dnmt1kd.6w=0",
+ "eb.dnmt3bkdhrad9.6w-cb.dnmt3bkd.6w=0",
+ "bc.dnmt1kd.8w-ac.vector.8w=0",
+ "cc.dnmt3bkd.8w-ac.vector.8w=0",
+ "dc.dnmt1kdhrad9.8w-bc.dnmt1kd.8w=0",
+ "ec.dnmt3bkdhrad9.8w-cc.dnmt3bkd.8w=0")))
summary(model.mc,test=adjusted(type="Westfall"))
######################
THE PROGRAM FROZE AT THIS POINT AND DID NOT RETURN ANYTHING
HERE IS MY SESSION INFO
######################
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6
Matrix products: default
BLAS:
/Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK:
/Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] multcomp_1.4-8 TH.data_1.0-9 MASS_7.3-50 survival_2.42-6
mvtnorm_1.0-8
loaded via a namespace (and not attached):
[1] zoo_1.8-3 compiler_3.5.1 Matrix_1.2-14 sandwich_2.4-0
codetools_0.2-15 splines_3.5.1 grid_3.5.1 lattice_0.20-35
#############################
Why would the summary function not work with 27 comparisons with Westfall but
work with 4 comparisons?
Why would the summary function not work with 27 comparisons with Westfall but
work with the same comparisons with Bonferroni?
Is the problem intrinsic to
A. Westfall’s , method with a large number of comarisons.
B, The impkementation of Westfall’s method in multcomp?
C. Machine requirements for Westfall’s method with so many comparisons?
D. My coding
E. Other.
I have used Westsall;’s method throught the paper which I am now working and
would prefer to use it for this
problem for consistency.
I would appreciate any advice.
Thanks and best wishes,
Rich
Richard A. Friedman, PhD
Associate Research Scientist,
Biomedical Informatics Shared Resource
Herbert Irving Comprehensive Cancer Center (HICCC)
Lecturer,
Department of Biomedical Informatics (DBMI)
Room 825
Irving Cancer Research Center
Columbia University Herbert and Florence Irving Medical Center
1130 St. Nicholas Ave
New York, NY 10032
(212)851-4765 (voice)
r...@cumc.columbia.edu<mailto:r...@cumc.columbia.edu>
http://www.columbia.edu/~raf4/index.html
In memoriam, Steve Ditko
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