[R-sig-ME] means , CIs from lmer, glmer

[Kornbrot, Diana]

I am keen to promote the use of generalised mixed models for the analysis of proportions to psychologists
Have straight fowl code in SPSS [costly] and would like to supply equivalent R Code without ‘tears’
Design is a follows raw frequencies are: FreqPos for ‘success’ and FreqNeg for ‘failure’
Predictors are Rab with 4 levels, repeated over participants and Between with 2 separate groups of participants
Model is binomial with logit link

Require following output to correspond to SPSS output from code below
Descriptive: Means, se and 95% CIs  by Rab, by Between and by Rab*Between
Inferential: fo  Rab, Between and  Rab*Between: F value, MSE, numerator df, denominator df [this enables p-values]

Have tried

logit1 <- glmer(cbind(FreqPos,FreqNeg) ~ Rab + Between + Rab*Between + (1| Participant), family=binomial(link="logit"))
gives F and MSE no denominator df or MSE. Different results to SPSS
nb F=MSE - that can’t be right F is supposed to be ratio of chi-squares

summary (logit1)
gives coefficients  and SEs. Different results to SPSS
also tried predicted and fitted but still no means

have spent days searching internet for examples - but none of them seem to show how to get the output I need

All help greatly appreciated

____
Spss syntax

*Generalized Linear Mixed Models.
GENLINMIXED
  /DATA_STRUCTURE SUBJECTS=Participant REPEATED_MEASURES=Rab COVARIANCE_TYPE=UNSTRUCTURED
  /FIELDS TARGET=FreqPos TRIALS=FIELD(Nmax)  OFFSET=NONE
  /TARGET_OPTIONS DISTRIBUTION=BINOMIAL LINK=LOGIT
  /FIXED  EFFECTS=Rab Between Rab*Between USE_INTERCEPT=TRUE
  /BUILD_OPTIONS TARGET_CATEGORY_ORDER=DESCENDING INPUTS_CATEGORY_ORDER=DESCENDING MAX_ITERATIONS=100 CONFIDENCE_LEVEL=95 DF_METHOD=SATTERTHWAITE COVB=MODEL PCONVERGE=0.000001(ABSOLUTE) SCORING=0 SINGULAR=0.000000000001
  /EMMEANS TABLES=Rab COMPARE=Rab CONTRAST=DEVIATION
   /EMMEANS TABLES=Between CONTRAST=NONE
   /EMMEANS TABLES=Rab*Between CONTRAST=NONE
  /EMMEANS_OPTIONS SCALE=ORIGINAL PADJUST=LSD.

best
Diana


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