1,409 questions
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14
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Longitudinal Analysis with High Variability in Time Entries per Subject
I am working with retrospective data from a symptom tracking app and I aim to identify different symptom trajectory classes within this data. After reviewing relevant literature, I have found that ...
- 1
2
votes
1
answer
45
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glmmTMB issue with number of observations and groups
I have a dataset with 125 animals across 3 sites and 100500 observations. Both show up properly when looking at the structure of the data but when I run the model with an updated data frame (I added a ...
- 23
-1
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0
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44
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step() and mixed model in R [closed]
I built my mixed models with function lme4::lmer() and lme4::glmer() and tried to do the stepwise method. Unfortunately step() or stepAIC() didn't work with lme4::lmer() neither lme4::glmer(). Did ...
0
votes
1
answer
65
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Why is glmer function for logistic regression taking so long to run in R?
I am running a multiple logistic regression model. The dataset has ~350,000 observations, with the outcome being a binary 0/1 dichotomous variable. Most predictors are also dichotomous but there are ...
0
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0
answers
24
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How to bootstrap ANOVA type 3 fixed effects of a linear mixed model in R (lme4)?
I've been trying to bootstrap a linear mixed model with three 2-level categorical fixed factors (and all two-way interactions), and one random factor.
I can get the linear mixed model to run, I can ...
0
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0
answers
65
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How to use emmeans for contrast/pairwise comparison when fixed-effect model matrix is rank deficient?
I have a data with 3 fixed effect factors G (two levels g1 and g2), V (two levels v1 and v2) and C (c1,c2,c3,c4,c5,c6,c7), and a random effect ID. I need to fit a linear mixed model or robust lmm with ...
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1
vote
0
answers
56
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How to deal with autocorrelation in piecewise growth curve model (linear mixed effect approach)
I'm running a piecewise growth curve model in R using nlme. I have nested data with seven repeated measures (saliva cortisol levels) for each of my subjects (no missing data). I have a "classic&...
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0
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0
answers
31
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Linear Mixed (Multilevel) Model: Predictors and outcomes at different timepoints
I'm analysing data from a randomised controlled trial, and want to predict a change in an outcome (reduction in anxiety scores from Baseline to Week 4), based on two predictors measured at the two ...
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1
vote
1
answer
71
views
Contrasting results about singularity in random intercept logistic model
I estimated a random intercept logistic regression model in R using the lme4::glmer function. The model converges without issues.
However, when producing post-estimation goodness of fit statistics ...
- 165
0
votes
1
answer
36
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How can I Interpret the slope of year variable?
I was trying to model the relationship between time and mean egg laying dates across multiple farms.
lmer(mean_egg_dates ~ scale (Years) + (1|region),
data = DF)
The time period ...
- 65
1
vote
1
answer
69
views
Integrating participant as a random effect into log linear / poisson model - in R
I want to include participants as a "random effect" into a log linear model (poisson model), to account for the variance between participants.
My data comes from a contingency table and I am ...
1
vote
0
answers
81
views
Fitting random matrix in mixed model [closed]
I checked many questions, but I did not find a solution for my problem. Here is the R-code:
set.seed(1234)
mat <- matrix(sample(0:1, size=1000, replace=TRUE), nrow=20)*2
rownames(mat) <- ...
- 11
0
votes
0
answers
19
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Model selection : how to deal with fixed and random effects in the same time?
I am studying the effect of various ecological variables on different plant species. I want to use GLM(M), but I am not very familiar with this approach.
After a preliminary correlation analysis and ...
1
vote
1
answer
33
views
Error plotting power curve with varying number of observations per cluster using SIMR in R
I'm using the simr package in R to conduct a power analysis for a two-level poisson regression model. I'm trying to plot a power curve to understand the influence of the number of observations per ...
- 187
0
votes
1
answer
77
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Simulating correlated random intercept and slope for mixed model data
I've written a data-generating function in R which simulates data used for hierarchical (multi-level) modeling. The function generates both fixed and random effects with correlated intercepts and ...
- 187