search for: pdcompsymm

Try this data(Assay) as1 <- lme(logDens~sample*dilut, data=Assay, random=pdBlocked(list( pdIdent(~1), pdIdent(~sample-1), pdIdent(~dilut-1)))) update(as1,random=pdCompSymm(~sample-1)) update(as1,random=pdCompSymm(~sample-1)) update(as1,random=pdCompSymm(~sample-1)) update(as1,random=pdCompSymm(~sample-1)) I'm getting different results on different invocations! _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status...

Dear R community, I have trouble implementing a nested variance-covariance matrix in the lme function. The model has two fixed effects called End and logpgc, the response variable is the logarithm to base 2 of Intensity ( log2(Intensity) ) and the random effects are called Probe and ProbeNo. The model has the following nesting structure: A Pixel is nested within the ProbeNo,the ProbeNo is

...pound symmetry variance-covariance structure for the random effects in a split-plot experiment on varieties of oats. I ran the codes from the book and extracted the variance and correlation components: >library(nlme) >data(Oats) >fm4OatsB <- lme(yield~nitro, data=Oats, random=list(Block=pdCompSymm(~Variety-1))) >VarCorr(fm4OatsB) Block = pdCompSymm(Variety - 1) Variance StdDev Corr VarietyGolden Rain 331.5271 18.20788 VarietyMarvellous 331.5271 18.20788 0.635 VarietyVictory 331.5271 18.20788 0.635 0.635 Residual 165.5585 12.866...

My question concerns the logic behind hypothesis tests for fixed-effect terms in models fitted with lme. Suppose the levels of Subj indicate a grouping structure (k subjects) and Trt is a two-level factor (two treatments) for which there are several (n) responses y from each treatment and subject combination. If one suspects a subject by treatment interaction, either of the following models seem

Dear all, I am trying to define my own corStruct which is different from the classical one available in nlme. The structure of this correlation is given below. I am wondering to know how to continue with this structure by using specific functions (corMatrix, getCovariate, Initialize,...) in order to get a structure like corAR1, corSymm which will be working for my data. Thanks in advance.

Hi al, I have a dataset (see attached), which basically involves 4 treatments for a chemotherapy drug. Samples were taken from 2 biopsy locations, and biopsy were taken at 2 time points. So each subject has 4 data points (from 2 biopsy locations and 2 time points). The objective is to study treatment difference.? I used lme to fit a mixed model that uses "biopsy.site nested within pid"