pdbailey0
commented
2 years ago @BernhardClemm thank you for the reproducible example. We have tried it on Windows and it works but I see you are using an Apple, so we will test there next. Have you tried upgrading to the latest R version, 4.1.2? If you want to stay with 4.0 you may want to upgrade to 4.0.5.
Also, notice the second warning.
> m1 <- mix(participation_bin ~ news_u_log + u_visits_log + (1 | person_id), dt,
+ weights=c("wave_weight", "weight"),
+ family = binomial(link="logit"))
Warning messages:
1: In mix(participation_bin ~ news_u_log + u_visits_log + (1 | person_id), :
There were 5 rows with missing data. These have been removed.
2: In mix(participation_bin ~ news_u_log + u_visits_log + (1 | person_id), :
Group variances too small to estimate accurately. The estimated variance in the group level terms(s) “person_id:(Intercept)” is near zero. Very low variance suggests that the data is not hierarchical and that a model without these levels should be considered. If this removes all groups then a non-hierarchical model, such as logistic regression, should be considered.
> summary(m1)
Call:
mix(formula = participation_bin ~ news_u_log + u_visits_log +
(1 | person_id), data = dt, weights = c("wave_weight",
"weight"), family = binomial(link = "logit"))
Variance terms:
Level Group Name Variance Std. Error Std.Dev.
2 person_id (Intercept) 0.1254 0.01672 0.3542
Groups:
Level Group n size mean wgt sum wgt
2 person_id 174 0.9215 160.3
1 Obs 517 1.0000 517.0
Fixed Effects:
Estimate Std. Error t value
(Intercept) 0.68552 1.06757 0.642
news_u_log 0.09744 0.05925 1.645
u_visits_log -0.12337 0.12820 -0.962
BernhardClemm
For a reproducible example, use these data:
Running a logistic model on outcome "participation_bin" causes my R to crash:
My version: