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

[Ben Bolker]

  Yes, that was a thinko on my part.  Thanks.

On 18-02-27 05:22 AM, Rune Haubo wrote:
> 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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>>> http://dianakornbrot.wordpress.com/
>>> http://go.herts.ac.uk/Diana_Kornbrot
>>> skype:  kornbrotme
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