CODEWITHSUNDEEP
lme4mixed-models
tnt
tnt

Reputation: 1459

include random slope in binomial mixed model

I am using a binomial GLMM to examine the relationship between presence of individuals (# hours/day) at a site over time. Since presence is measured daily for several individuals, I've included a random intercept for individual ID.

e.g., 

presence <- cbind(hours, 24-hours)
glmer(presence ~ time + (1 | ID), family = binomial)

I'd like to also look at using ID as a random slope, but I don't know how to add this to my model. I've tried the two different approaches below, but I'm not sure which is correct.

glmer(presence ~ time + (1 + ID), family = binomial)
Error: No random effects terms specified in formula

glmer(presence ~ time + (1 + ID | ID), family = binomial)
Error: number of observations (=1639) < number of random effects (=5476) for term (1 + ID | ID); the random-effects parameters are probably unidentifiable

Upvotes: 0

Views: 2386

Answers (1)

arranjdavis
arranjdavis

Reputation: 735

You cannot have a random slope for ID and have ID as a (level-two) grouping variable (see this documentation for more detail: https://cran.r-project.org/web/packages/lme4/lme4.pdf).

The grouping variable, which is ID in the models below, is used as a variable for which to specify random effects. model_1 gives random intercepts for the ID variable. model_2 gives both random intercepts and random slopes for the time variable. In other words, model_1 allows the intercept of the relationship between presence and time to vary with ID(the slope remains the same), whereas model_2 allows for the both the intercept and slopes to vary with ID, so that the relationship between presence and time (i.e., the slope) can be different for each individual (ID).

model_1 = glmer(presence ~ time + (1 | ID), family = binomial)

model_2 = glmer(presence ~ time + (1 + time | ID), family = binomial)

I would also recommend:

Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: an introduction to basic and advanced multilevel modeling (2nd ed.): Sage.

Upvotes: 3

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