R 2.8.1
Windows XP
I am trying to analyze repeated measures data (the data are listed at the end
of this Email message) and I need help to make sure that I have properly
specified my model, and would like to know why lmer does not return a p value
for Group, my fixed effect.
My subjects are divided into two groups (variable GROUP), individual subjects
are indicated by the variable SS, Value is the outcome measure, each subject
has Value measured three times.
I have used the following code:
fit1<-lmer(Value~Group+(1|SS),data=smallDS)
print(fit1)
Linear mixed model fit by REML
Formula: Value ~ Group + (1 | SS)
Data: Dataset
AIC BIC logLik deviance REMLdev
284.8 290.4 -138.4 291.4 276.8
Random effects:
Groups Name Variance Std.Dev.
SS (Intercept) 1038.0 32.218
Residual 552.7 23.510
Number of obs: 30, groups: SS, 10
Fixed effects:
Estimate Std. Error t value
(Intercept) 152.87 15.63 9.778
Group[T.ContSIRNAnoEGF] -15.87 22.11 -0.718
Correlation of Fixed Effects:
(Intr)
G[T.CSIRNAE -0.707
Questions:
(1) Have I set up lmer properly to analyze the repeated measures data?
(2) How can I get a p value for Group, my fixed effect?
Group SS Value
[1,] 2 1 127
[2,] 2 1 179
[3,] 2 1 159
[4,] 2 2 186
[5,] 2 2 173
[6,] 2 2 178
[7,] 2 3 117
[8,] 2 3 116
[9,] 2 3 70
[10,] 2 4 176
[11,] 2 4 149
[12,] 2 4 138
[13,] 2 5 100
[14,] 2 5 105
[15,] 2 5 82
[16,] 1 6 142
[17,] 1 6 195
[18,] 1 6 222
[19,] 1 7 218
[20,] 1 7 178
[21,] 1 7 147
[22,] 1 8 135
[23,] 1 8 162
[24,] 1 8 177
[25,] 1 9 104
[26,] 1 9 102
[27,] 1 9 121
[28,] 1 10 135
[29,] 1 10 121
[30,] 1 10 134
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
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