[R-sig-ME] What p value should I report here?

[Ben Bolker]

  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
> 
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> 
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