[R] logit regression, test among groups
Frank E Harrell Jr
fharrell at virginia.edu
Tue May 28 14:31:41 CEST 2002
I do this by getting two predicted values and the design matrix for each (to get standard errors). In the Design library you can do
f <- lrm(p.a ~ spp*log(light))
contrast(f, list(spp=3,light=1), list(spp=2,light=1))
# Contrasts spp=3 vs spp=2 to get odds ratio, setting light=1
You can also request that contrast give you a vector of contrasts for varying light.
You could also do this task with glm. I don't like to refit models just to get desired contrasts. Predicted values go a long way.
On Tue, 28 May 2002 06:59:23 -0400
"Martin Henry H. Stevens" <HStevens at muohio.edu> wrote:
> Dear all:
> My logistic regression model includes one qualitative and one quantitative
> predictor variable,
> aes <- glm(p.a ~ spp * log(light), family=binomial(link=logit)),
> where spp is abundance of 3 species and light is subcanopy light
> availability varying from 0 1.
> I want to test differences among levels of the quantitative variable at a
> value of x other than the current log(light)=0. I tried using
> I(log(light+.5)) but this caused serious lack of fit (AIC went from 1574 to
> 1656, and diagnostic plots demonstrated poor fit). How would create a model
> statement such that I test differences among groups at log(light)=approx. 2?
> Many thanks.
> Martin Henry H. Stevens, Assistant Professor
> 338 Pearson Hall
> Botany Department
> Miami University
> Oxford, OH 45056
> Office: (513) 529-4206
> Lab: (513) 529-4262
> FAX: (513) 529-4243
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Frank E Harrell Jr Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat
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