Covers the basics of mixed models, mostly using @lme4
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Updated
Jan 30, 2022 - R
Covers the basics of mixed models, mostly using @lme4
A document introducing generalized additive models.📈
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
Mixed models @lme4 + custom covariances + parameter constraints
Mixed-effect model to test differences in cell type proportions from single-cell data, in R
Workshop on using Mixed Models with R
👓 Functions related to R visualizations
Functions for using mgcv for mixed models. 📈
An R package for extracting results from mixed models that are easy to use and viable for presentation.
An R package for I-prior regression
Demonstration of alternatives to lme4
Stata and R programs to automatically quasi-demean regressors following FGLS-RE or MLE-RE regression
a meta-analysis on the effect of intravenous magnesium on myocardial infarction
Raw files for a document providing an overview of mixed models from varying perspectives.
Illustrate CR models with individual heterogeneity (multistate, random-effect, finite-mixture)
Monte Carlo Simulation comparing the performance of various estimators for panel data with binary dependent variable models
Using Fixed Effect, Random Effect and Hausman Taylor IV to estimate the impacts on wage
Fit band-recovery models with temporal random effects
Pitch Adjusted Swipe Rate Above Average (pSRAA)
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