What p value should I report here?
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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