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

[Rune Haubo]

Just a small note that lmerTest (and the Satterthwaite method for
degrees of freedom) is only meaningful for _linear_ mixed models - not
for the generalized variants such as the one considered here for
proportions.

Best,
Rune

On 27 February 2018 at 02:02, Ben Bolker <bbolker at gmail.com> wrote:
>   Hi Diana,
>
> A reproducible example is always helpful/increases your chances of
> getting a useful answer ...
> It might help if you included the SPSS output (or posted it somewhere
> -- note that this list doesn't take HTML-formatted messages nor most
> attachments), as many of us don't have access to it.
>
> Look into the (very well-documented) emmeans package:
> https://CRAN.R-project.org/package=emmeans
> and the lmerTest package (for Satterthwaite df approximations)
>
> On Mon, Feb 26, 2018 at 12:11 PM, Kornbrot, Diana
> <d.e.kornbrot at herts.ac.uk> wrote:
>> 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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