Hi,
I am new to R (and not really a stats expert) and am having trouble
interpreting its output. I am running a human learning experiment, with
6 scores per subject in both the pretest and the posttest. I believe I
have fitted the correct model for my data- a mixed-effects design, with
subject as a random factor and session (pre vs post) nested within group
(trained vs control).
I am confused about the output. The summary command gives me this table:
> D.lme<- lme(score~GROUP/session, random=~1|subject, data=ILD4L )
> summary(D.lme)
Linear mixed-effects model fit by REML
Data: ILD4L
Subset: EXP == "F"
AIC BIC logLik
-63.69801 -45.09881 37.84900
Random effects:
Formula: ~1 | subject
(Intercept) Residual
StdDev: 0.1032511 0.1727145
Fixed effects: score ~ GROUP/session
Value Std.Error DF t-value p-value
(Intercept) 0.10252778 0.05104328 152 2.008644 0.0463
GROUPT 0.09545347 0.06752391 12 1.413625 0.1829
GROUPC:sessionpost -0.00441389 0.04070919 152 -0.108425 0.9138
GROUPT:sessionpost -0.23586042 0.03525520 152 -6.690090 0.0000
Correlation:
(Intr) GROUPT GROUPC
GROUPT -0.756
GROUPC:sessionpost -0.399 0.301
GROUPT:sessionpost 0.000 -0.261 0.000
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-2.66977386 -0.52935645 -0.08616759 0.57215015 3.26532101
Number of Observations: 168
Number of Groups: 14
I believe the fixed-effects section of this output to be telling me that
my model intercept (which I assume to be the control group pretest?) is
significantly different from 0, and that GROUPT (i.e. the trained group)
does not differ significantly from the intercept- therefore no pretest
difference between groups?
The next line is, I believe showing that the GROUPC x sessionpost
interaction (i.e., control posttest scores?) is not significantly
different from the intercept (i.e. control pretest scores). Finally, I
am interpreting the final line as indicating that the GROUPT x
sessionpost interaction (ie, trained posttest scores?) is significantly
different from the trained pretest scores (GROUPT). A treatment contrast
that I would like to apply would be for Control-post vs Trained-post, to
see if the groups differ after training, but I'm not sure how to do
this- and I feel I am probably overcomplicating the matter.
also,
I am confused about how to report this output in my publication. For
instance, what should I be reporting for df? Those found on the output
of the anova table?
Would it be possible to look through this for me and indicate how to
interpret the R output, and also how I should be reporting this?
Apologies for asking such basic questions, but I would like to start
using R more regularly and to make sure I am doing so correctly.
Many thanks,
Dan
