This is in “lme4: Mixed-Effect modeling with R” by Douglas M. Bates, which is in general really great (if sometimes confusingly written), but this is just plain wrong isn't it?

#stats #maths #R #lme4

I have written a book draft of an introduction to #multilevel modeling, entitled #Multilevel Thinking: https://agrogan1.github.io/multilevel-thinking/. Comments, questions and corrections are appreciated, as are suggestions for a possible publisher.

While applicable to many different software programs, the book is currently centered around the use of #Stata, but I hope to extend it to use of #rstats (#lme4) and #julialang

the phrase “i need to figure out how to sandwich the glmer” was not something i expected to text a friend on a sunday morning #rstats #lme4 #gtsummary

A mixed effects question for you #rstats #lme4 people: Persons are organised in groups for some time. No movement between groups. We have self-ratings of a Trait, and all persons in the group rate all other persons in the same group on a Behavior (but larger n/groups than in the picture). I want to predict Behavior by Trait. My first thought is a linear mixed-effects model with two random terms: Behavior ~ Trait + (1 | Subject) + (1 | Rater) Would that work? This is new territory for me.

What's the standard package in Python for doing #MixedEffectsModels instead of #R? I need to use Python unfortunately but want something with #lme4 / #lmer / #brms functionality

Our research group is doing a seminar the coming week, and I've been asked to hold a one-hour intro to quantitative diary studies and #multilevel analyses for new #phd students unfamiliar with this way of collecting data. I'd like to highlight benefits, when it's appropriate, show an example using #rstats and #lme4, and start a discussion around how they can do this themselves in their projects.

Does anyone have suggestions for stuff to include, or clever ways to convey it? Resources?

@Mattalica1972 After starting to feel comfortable with the language in general I’d just Google tutorials or read manuals/vignettes of packages that do the stuff you actually need to do, like #lme4 for multilevel or #lavaan for SEM. Also, Googling “How do I [insert thing you want to do here] in R?” dozens of times while you work is a 100% legitimate way of learning #rstats.

Do any of you guys have a good example of application of mixed models, on a publicly available dataset? #rstats #lme4 #lmm #linearMixedModel