1
vote
0answers
17 views

Partitioning variance from logistic regression

Short version How can I partition the variance from the different levels in a nested mixed-effects logistic regression? Preferably using R, but even general principles would be helpful as a start. ...
0
votes
0answers
60 views

Use predicted values with or without random part to plot Residuals with binnedplot of a logistic regression in glmer (lme4 package) in R?

Which binnedplot of the glmer should I use to check the model? The residuals against the predicted values without random part(REform=NA) or residuals against the predicted values with random ...
0
votes
1answer
49 views

Cross-validation for mixed-effect logistic regression? [duplicate]

I would like to use cross-validation to test how predictive my mixed-effect logistic regression model is (model run with glmer). Is there an easy way to do this using a package in R? I've only seen ...
1
vote
1answer
75 views

Mixed-effect logistic regression in R - questions

I am new to R, and don't see these questions answered anywhere in documentation (though I could be wrong). I am using the following nomenclature to run my mixed-effects logistic regression, based on ...
9
votes
0answers
123 views

Inference on fixed effects in a mixed effects model

I have correlated data and am using a logistic regression mixed effects model to estimate the individual level (conditional) effect for a predictor of interest. I know that for standard marginal ...
2
votes
1answer
79 views

Large errors for logistic regression, what does it mean?

I run the following scripts in r for mixed effect logistic regression. ...
0
votes
1answer
124 views

Logistic regressioin - contradictory results?

I am using the glmer method in lme4 to build a mixed effect logistic regression model, the model is as follows: ...
1
vote
0answers
105 views

Inference for between group differences (with non-linear time component, outliers and mixed effects)

TLDR: How can I perform inference for the between group differences in a possibly logistic growth with time in the presence of outliers, unequal measurement times and frequency, bounded measurements ...
1
vote
1answer
136 views

How to fit a logistic regression for 1 dependent variable and 1 qualitative variable measured twice

I am struggling to fit a simple logistic regression for one dependent value (group) by one independent qualitative variable (dilat) measured twice independently (rater). I try many solutions and ...
0
votes
0answers
55 views

Comparison with trial dependent chance level

I ran an experiment where each participant had to choose 1 image from a 4-image display and I measured whether the image they chose was from category A. I want to compare the average proportion of ...
0
votes
1answer
67 views

Interpretation of probabilities from a mixed-model logistic regression

In the following model specification, which is a random intercept 2-level logistic regression: Would two lower level units ($i$) with the same value of $x_{1ij}$ and within the same higher level ...
2
votes
0answers
83 views

Logistic Regression - Predicting an event with a couple time-related issues

I'm using logistic regression to predict the occurrence of tree carcasses falling after a mortality event. Data include a variety of topographic and tree characteristic variables and also time since ...
1
vote
0answers
156 views

Are there packages for fitting ordinal logistic/probit mixed models with random slopes in R?

I'm looking for a way to fit an ordinal logistic and/or probit mixed model that includes random slopes. The only package for R I could find that allows for random effects at all in ordinal mixed ...
3
votes
1answer
152 views

Which model to use with repeated measures data that contains multiple binary dependent variables

What model should I use??? I have daily repeated measures data. It has multiple dependent presence absence variables, (of which, I have collapsed into a CA with continuous variables of CA1 & ...
11
votes
3answers
11k views

How to interpret main effects when the interaction effect is not significant?

I ran a Generalized Linear Mixed Model in R and included an interaction effect between two predictors. The interaction was not significant, but the main effects (the two predictors) both were. Now ...
1
vote
0answers
297 views

What are the assumptions of ordinal mixed effects logistic regression?

Specifically, what are the assumptions of ordinal mixed effect logistic regression performed with the "ordinal" package in R? I just got knobbled by a reviewer because these weren't clearly stated in ...
3
votes
1answer
806 views

Interpreting coefficients of ordinal logistic regression when there is clustering within the data

I have built and refined a regression model using the ordinal package in R. The measure is $0>1>2>3>4>5$ (Yes/No ...
4
votes
0answers
198 views

Crossed random effects and unbalanced data

I am modeling some data where I think I have two crossed random effects. But the data set is not balanced, and I'm not sure what needs to be done to account for it. My data is a set of events. An ...
10
votes
1answer
4k views

What is the difference between generalized estimating equations and GLMM?

I'm running a GEE on 3-level unbalanced data, using a logit link. How does this differ (in terms of the conclusions I can draw and the meaning of the coefficients) from a GLM with mixed effects ...
5
votes
2answers
853 views

Analyzing a 2x3 repeated measures design using a logit mixed model

An experiment I conducted recently used a 2 (between participants) x 3 (within participants) design. That is, participants were randomly allocated to one of two conditions, and then completed three ...