From: R Heberto Ghezzo, Dr <heberto.ghezzo_at_mcgill.ca>

Date: Thu 03 Aug 2006 - 03:48:33 EST

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu Aug 03 07:01:08 2006

Date: Thu 03 Aug 2006 - 03:48:33 EST

-----Original Message-----

From: r-help-bounces@stat.math.ethz.ch on behalf of Spencer Graves
Sent: Wed 8/2/2006 4:25 AM

To: Grathwohl, Dominik, LAUSANNE, NRC-BAS
Cc: r-help@stat.math.ethz.ch; Torsten Hothorn
Subject: Re: [R] Correlation adjusted Bonferroni? (was: Multiple tests on repeated measurements)

p.value.raw p.value.bon p.value.adj = raw.p = bon.p =multcomp.p "bon.cor.p"diff/v=0 0.028572509 0.057145019 0.054951102 0.034934913 diff/v=1 0.001727993 0.003455987 0.003415545 0.002119276

Hope this helps. Spencer Graves

Grathwohl, Dominik, LAUSANNE, NRC-BAS wrote:

> Dear R-helpers:

*>
**> My question is how do I efficient and valid correct for multiple tests in a repeated measurement design:
**> Suppose we measure at two distinct visits with repeated subjects a treatment difference on the same variable.
**> The treatment differences are assessed with a mixed model and adjusted by two methods for multiple tests:
**>
**> # 1. Method: Adjustment with library(multcomp)
**>
**> library(nlme)
**> library(multcomp)
**>
**> n <- 30 # number of subjects
**> sd1 <- 0.5 # Standard deviation of the random intercept
**> sd2 <- 0.8 # Standard deviation of the residuals
**> id <- rep(1:n,times=2); v <- rep(0:1, each=n); trt <- rep(sample(rep(0:1, each=n/2), n), times=2)
**> df <- data.frame(id, v, trt,
**> y=2 + rep(rnorm(10,0,sd1), times=2) + 0.5*v + 0.7*trt + 0.2*v*trt + rnorm(2*n, 0, sd2))
**> m1 <- lme(y ~ v + trt + v*trt, data=df, random= ~ 1|id)
**> summary(m1)
**> par4 <- m1$coef$fixed
**> cov4 <- vcov(m1)
**> cm4 <- matrix(c(0, 0, 1, 0, 0, 0, 1, 1), nrow = 2, ncol=4, byrow=TRUE,
**> dimnames = list(c("diff/v=0", "diff/v=1"), c("C.1", "C.2", "C.3", "C.4")))
**> v4 <- csimint(estpar=par4, df=n-6, # I'm not sure whether I found
**> # the correct degrees of freedom
**> covm=cov4,
**> cmatrix=cm4, conf.level=0.95)
**> sv4 <- summary(v4)
**>
**> # 2. Method: I found in Handbook of Statistics Vol 13, p.616,
**> # same can be found in http://home.clara.net/sisa/bonhlp.htm
**> # Bonferroni on correlated outcomes:
**>
**> raw.p <- sv4$p.value.raw
**> co4 <- cor(df$y[df$v==0],df$y[df$v==1])
**> rho <- mean(c(1,co4,co4,1))
**> pai <- 1-(1-raw.p)^2^(1-rho)
**>
**> # The results of two methods are presented in the following lines:
**> out <- cbind(raw.p, sv4$p.value.bon, sv4$p.value.adj, pai)
**> colnames(out) <- c("raw.p", "bon.p", "multcomp.p", "bon.cor.p")
**> out
**>
**> As you can see there are quite big differences
**> between the two ways adjusting for multiple tests on repeated measurements.
**> I guess that the multcomp library is not appropriate for this kind of hypotheses.
**> However I could not find an explanation in the help files.
**> May be one of the experts can point me in the right direction?
**>
**> Kind regards,
**>
**> Dominik
**>
**> platform i386-pc-mingw32
**> arch i386
**> os mingw32
**> system i386, mingw32
**> status
**> major 2
**> minor 2.1
**> year 2005
**> month 12
**> day 20
**> svn rev 36812
**> language R
**>
**> [[alternative HTML version deleted]]
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
*

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu Aug 03 07:01:08 2006

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