[R-sig-ME] What p value should I report here?
Ben Bolker
bbo|ker @end|ng |rom gm@||@com
Fri May 3 04:53:24 CEST 2019
What we'd like to see is the *results* of summary(Vert_effect) and
summary(model.frame(glmm_Vert_effect)) ... for example, if I was running
the first example in ?lmer, the desired output would look something like
this (here, the two outputs are identical because there are no NA values
in the input).
> library(lme4)
Loading required package: Matrix
> fm1 <- lmer(Reaction~Days+(1|Subject), sleepstudy)
> summary(sleepstudy)
Reaction Days Subject
Min. :194.3 Min. :0.0 308 : 10
1st Qu.:255.4 1st Qu.:2.0 309 : 10
Median :288.7 Median :4.5 310 : 10
Mean :298.5 Mean :4.5 330 : 10
3rd Qu.:336.8 3rd Qu.:7.0 331 : 10
Max. :466.4 Max. :9.0 332 : 10
(Other):120
> summary(model.frame(fm1))
Reaction Days Subject
Min. :194.3 Min. :0.0 308 : 10
1st Qu.:255.4 1st Qu.:2.0 309 : 10
Median :288.7 Median :4.5 310 : 10
Mean :298.5 Mean :4.5 330 : 10
3rd Qu.:336.8 3rd Qu.:7.0 331 : 10
Max. :466.4 Max. :9.0 332 : 10
(Other):120
On 2019-05-02 10:51 p.m., DESPINA MICHAILIDOU wrote:
> The code is
>
> glmm_Vert_effect <- glmer(Vert_effect ~ P-Diz-today + (1|
> ID/SCAN_DATE/Side), data=GCA_data, family=binomial(link= "logit"))
>
> summary(Vert_effect).
>
>
> That is your question?
>
>
> I am sorry i am very new to R.
>
>
> Thank you for your interest and help. Really appreciate it.
>
>
> Despina
>
>
> Στις Πέμ, 2 Μαΐ 2019 στις 10:40 μ.μ., ο/η Ben Bolker <bbolker using gmail.com
> <mailto:bbolker using gmail.com>> έγραψε:
>
>
> We will be able to help much better if you can provide a reproducible
> example, or at least the results of the summary() commands requested
> below ...
>
> On 2019-05-02 10:29 p.m., DESPINA MICHAILIDOU wrote:
> > Yes you are correct. I have a 0 or 1 scoring outcome. I do have some
> > blanks in my observations. Thank you for your response.
> >
> > Despina
> >
> > Στις Πέμ, 2 Μαΐ 2019 στις 10:19 μ.μ., ο/η Ben Bolker
> <bbolker using gmail.com <mailto:bbolker using gmail.com>
> > <mailto:bbolker using gmail.com <mailto:bbolker using gmail.com>>> έγραψε:
> >
> >
> > Can you show us summary(GCA_data) and
> > summary(model.frame(fitted_model)) please? It looks like for
> some reason
> > (maybe because of observations dropped due to NA values?) you
> have no
> > variation in your predictor variable (P_Diz_today).
> >
> > It's also potentially problematic that you have an
> observation-level
> > random effect for a Bernoulli outcome (i.e., you're fitting a
> binomial
> > model with a single-column value as the response and no weights=
> > argument, which implies you have a 0/1 outcome; you have the
> same number
> > of groups in your fully nested [ID:Scan:Side] random effect as
> > observations), but I don't think this would lead to the
> dropping of the
> > P_Diz_today predictor ...
> >
> > cheers
> > Ben Bolker
> >
> > On 2019-05-02 3:30 p.m., DESPINA MICHAILIDOU wrote:
> > > Hi everyone,
> > >
> > >
> > > I am running this regression analysis model and I get the
> > following output.
> > > What P value should I report for my variable P-Dizz today?What
> > does it mean
> > > that fixed-effect model matrix is rank deficient so dropping 1
> > column /
> > > coefficient? Can anyone help me with the interpretation of
> those data?
> > >
> > >
> > > Thank you in advance.
> > >
> > >
> > > Despina
> > >
> > >
> > > Generalized linear mixed model fit by maximum likelihood
> (Laplace
> > > Approximation) ['glmerMod']
> > >
> > > Family: binomial ( logit )
> > >
> > > Formula: Vert_effect ~ P_Diz_today + (1 | ID/SCAN_DATE/Side)
> > >
> > > Data: GCA_data
> > >
> > >
> > >
> > > AIC BIC logLik deviance df.resid
> > >
> > > 80.3 94.5 -36.1 72.3 254
> > >
> > >
> > >
> > > Scaled residuals:
> > >
> > > Min 1Q Median 3Q Max
> > >
> > > -0.012501 -0.000639 -0.000639 -0.000639 0.105723
> > >
> > >
> > >
> > > Random effects:
> > >
> > > Groups Name Variance Std.Dev.
> > >
> > > Side:(SCAN_DATE:ID) (Intercept) 1502.7 38.76
> > >
> > > SCAN_DATE:ID (Intercept) 0.0 0.00
> > >
> > > ID (Intercept) 235.1 15.33
> > >
> > > Number of obs: 258, groups: Side:(SCAN_DATE:ID), 258;
> > SCAN_DATE:ID, 130;
> > > ID, 52
> > >
> > >
> > >
> > > Fixed effects:
> > >
> > > Estimate Std. Error z value Pr(>|z|)
> > >
> > > (Intercept) -14.711 3.646 -4.035 5.47e-05 ***
> > >
> > > ---
> > >
> > > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> > >
> > > fit warnings:
> > >
> > > fixed-effect model matrix is rank deficient so dropping 1
> column /
> > > coefficient
> > >
> > > convergence code: 0
> > >
> > > boundary (singular) fit: see ?isSingular
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > _______________________________________________
> > > R-sig-mixed-models using r-project.org
> <mailto:R-sig-mixed-models using r-project.org>
> > <mailto:R-sig-mixed-models using r-project.org
> <mailto:R-sig-mixed-models using r-project.org>> mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> > >
> >
> > _______________________________________________
> > R-sig-mixed-models using r-project.org
> <mailto:R-sig-mixed-models using r-project.org>
> > <mailto:R-sig-mixed-models using r-project.org
> <mailto:R-sig-mixed-models using r-project.org>> mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
>
More information about the R-sig-mixed-models
mailing list