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
???? ???, 2 ??? 2019 ???? 10:40 ?.?., ?/? Ben Bolker <bbolker at gmail.com
<mailto:bbolker at gmail.com>> ??????:
? 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
>
> ???? ???, 2 ??? 2019 ???? 10:19 ?.?., ?/? Ben Bolker
<bbolker at gmail.com <mailto:bbolker at gmail.com>
> <mailto:bbolker at gmail.com <mailto:bbolker at gmail.com>>> ??????:
>
>
>? ? ?? 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]]
>? ? ?>
>? ? ?> _______________________________________________
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