From: Maya Joshi <maya.d.joshi_at_gmail.com>

Date: Mon, 18 Apr 2011 06:14:51 -0400

R-help_at_r-project.org 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 Mon 18 Apr 2011 - 10:35:31 GMT

Date: Mon, 18 Apr 2011 06:14:51 -0400

Let me clarify the output I want to create:

Source X1 (var) X2 (var) X1&X2 (cov) gen var(X1) var(X2) cov(x1X2) block var(X1) var(X2) cov(x1x2) error/ res var(x1) var(x2)cov(x1x2)

I need to do posterior analysis out of this table

Thanks in advance

Maya

On Sun, Apr 17, 2011 at 9:59 PM, Maya Joshi <maya.d.joshi_at_gmail.com> wrote:

> Dear list

*>
**> I need your help: Execuse me for my limited R knowledge.
**>
**> #example data set
**> set.seed (134)
**> lm=c(1:4)
**>
**> block = c(rep(lm,6))
**>
**> gen <- c(rep(1, 4), rep(2, 4), rep(3, 4), rep(4, 4),rep(5, 4),rep(6, 4))
**>
**> X1 = c( rnorm (4, 10, 4), rnorm (4, 12, 6), rnorm (4, 10, 7),rnorm (4, 5,
**> 2), rnorm (4, 8, 4), rnorm (4,7, 2))
**>
**> X2 = X1 + rnorm(length(X1), 0,3)
**>
**> yvar <- c(X1, X2)
**>
**> X <- c(rep( 1, length(X1)), rep( 2, length(X2))) # dummy x variable
**>
**> dataf <- data.frame(as.factor(block), as.factor(gen), as.factor(X), yvar )
**>
**>
**>
**> My objective to estimate variance-covariance between two variables X1 and
**> X2. Means that I need to fit something like unstructure (UN) covariance
**> structure.
**>
**>
**>
**> Question 1: I got the following error
**>
**> require("lme4");
**>
**> fm1Gen <- lmer(yvar ~ X + gen +(1|block), data= dataf) # Question 1:
**> should I consider X fixed or random
**>
**>
**>
**> Error in model.frame.default(data = dataf, formula = yvar ~ X + gen + :
**> variable lengths differ (found for 'gen')
**>
**>
**>
**> A tried nlme too.
**>
**> require(nlme)
**>
**> fm2Gen <- lme(yvar ~ X + gen, random= ~ 1|block, data= dataf)
**>
**> Error in model.frame.default(formula = ~yvar + X + gen + block, data =
**> list( :
**> variable lengths differ (found for 'gen') # similar error
**>
**>
**>
**> Question 2: How can get I covariance matrix between X1 and X2 either using
**> lme4 or lmer.
**>
**> X1 X2
**>
**> X1 Var (X1) Cov(X1,X2)
**>
**> X2 Cov(X1, X2) Var(X2)
**>
**>
**>
**> Should I put gen in the model to do this? Should I specify something in "*
**> correlation* = "
**>
**> Thank you for your time
**>
**> Maya
**>
**>
**>
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*

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