Dear R experts,
I am running gls models with heterogeneous group variances using the glm
function in the nlme package with varIdent weights. I am interested in
controlling the baseline level for the group variance function standard
deviation estimates by applying the relevel function to the group variable.
When I use relevel, the baseline level in the coefficient table changes as
expected, but the baseline level does not change for the variance function
table; for example, see the fitted models gls1 vs. gls2 in the contrived
example below. Does anyone have a suggestion as to how I can change the
baseline level for the variance function output please? In addition to the
example below, I have tried specifying the value argument as per the varIdent
help page, e.g. variIdent(c(no=0.5), form = ~1|group) and have google searched
/ checked help pages for solutions without success.
I am running R version 3.1.0 on an iMac OSX v. 10.9.5
Thank you in advance
John Kornak
> library(nlme)
> group <- factor(c(rep("no",20),rep("yes",20)))
> set.seed(2)
> outcome <- c(rnorm(20,0,2),rnorm(20,5,4))
> dataTest <- data.frame(outcome,group)
# Original model fit before releveling
> gls1 <- gls(outcome ~ group, weights=varIdent(form = ~1|group), data=dataTest)
> summary(gls1)
� snip �
Variance function:
Structure: Different standard deviations per stratum
Formula: ~1 | group
Parameter estimates:
no yes
1.00000 2.23034
Coefficients:
Value Std.Error t-value p-value
(Intercept) 0.390922 0.4734001 0.825775 0.4141
groupyes 4.607951 1.1571140 3.982279 0.0003
�snip �
Residual standard error: 2.11711
Degrees of freedom: 40 total; 38 residual
# relevel the group so that �yes� is the reference
> dataTest$group <- relevel(dataTest$group,"yes")
> gls2 <- gls(outcome ~ group, weights=varIdent(form = ~1|group), data=dataTest)
> summary(gls2)
� snip �
Variance function:
Structure: Different standard deviations per stratum
Formula: ~1 | group
Parameter estimates:
no yes
1.00000 2.23034 ### �no" is still the reference group here for
the variance function
Coefficients:
Value Std.Error t-value p-value
(Intercept) 4.998873 1.055843 4.734484 0e+00
groupno -4.607951 1.157114 -3.982279 3e-04 # �yes� has become the
reference for the coefficients
� snip �
Residual standard error: 2.11711
Degrees of freedom: 40 total; 38 residual
>
---------------------------------------------------
John Kornak, PhD
Associate Professor in Residence
Department of Epidemiology and Biostatistics
University of California, San Francisco
Mission Hall: Global Health & Clinical Sciences Building
550 16th St, 2nd floor, Box #0560
San Francisco, CA 94158-2549
Tel: 415-514-8028
Fax: 415-514-8150
Email: john.kor...@ucsf.edu<mailto:john.kor...@ucsf.edu>
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