I am trying to run mixed models (logistic regression) on a dataframe with the glmer function from lme4 but I always receive this message: "boundary (singular) fit: see ?isSingular"
Even if I create a model with just an intercept and and the simplest random part (random intercept for one factor), the variance for this random factor is 0.
Family: binomial ( logit ) Formula: PointGagneparleServeur ~ 1 + (1 | Tour) Data: DataModel_Logit_allRF_AusOpen AIC BIC logLik deviance df.resid 480.7822 488.5765 -238.3911 476.7822 362 Random effects: Groups Name Std.Dev. Tour (Intercept) 0 Number of obs: 364, groups: Tour, 6 Fixed Effects: (Intercept) 0.5639 convergence code 0; 1 optimizer warnings; 0 lme4 warnings
Though I have observations for all the values of the factor :
table(DataModel_Logit_allRF_AusOpen$PointGagneparleServeur,DataModel_Logit_allRF_AusOpen$Tour) 1erTour 2emeTour 3emeTour 8eme Quart Demi 0 26 24 12 35 20 15 1 40 36 37 59 32 28
and the dependent variable PointGagneparleServeur is actually numeric.
(FYI, i recently "upgraded" my os to Catalina 10.15. Experiencing several bugs with other(non programming) softwares since. So, I am mentionning it just in case it could play a role...)
Does anyone have an idea on why I have this issue ?