[R] covariance matrix: a erro and simple mixed model question, but id not know answer sorry

From: Maya Joshi <maya.d.joshi_at_gmail.com>
Date: Sun, 17 Apr 2011 21:59:00 -0400


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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