On Thu, Jul 23, 2009 at 9:02 AM, John Sorkin<[email protected]> wrote: > 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. >
The model looks appropriate to me. If you had more repeated measures within subjects you might want to model the temporal correlation by structuring the within-subject error covariance; the correlation argument to nlme::lme accepts a variety of corClasses for this purpose (e.g. AR1). FAQ 7.35 provides a link to one explanation for why lmer omits p-values: https://stat.ethz.ch/pipermail/r-help/2006-May/094765.html However in your balanced, normal case you can get (in this case identical) p-values using eith aov or lme: fit2 <- aov(Value ~ Group + Error(SS), data = smallDS) #or library(nlme) fit3 <- lme(Value ~ Group, data = smallDS, random = ~1|SS) As you might have suspected from the lmer t-value close to 0, the associated p-value is about .5. hth, Kingsford Jones > 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) > > Confidentiality Statement: > This email message, including any attachments, is for th...{{dropped:6}} > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
