Illustrate CR models with individual heterogeneity (multistate, random-effect, finite-mixture)
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Updated
Nov 17, 2016 - R
Illustrate CR models with individual heterogeneity (multistate, random-effect, finite-mixture)
Cluster-specific logistic regression models for whether an NBA team will make the playoffs given the current statistics of that team. Specifically uses population averaged models (PA) based on generalized estimating equations (GEE); Also, uses cluster-specific (each team) random effects models
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)
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.
An R package for extracting results from mixed models that are easy to use and viable for presentation.
Functions for using mgcv for mixed models. 📈
👓 Functions related to R visualizations
Workshop on using Mixed Models with R
Testing differences in cell type proportions from single-cell data.
Mixed models @lme4 + custom covariances + parameter constraints
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
A document introducing generalized additive models.📈
Covers the basics of mixed models, mostly using @lme4
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