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Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
ggplot-based graphics and useful functions for GAMs fitted using the mgcv package
Covers the basics of mixed models, mostly using @lme4
A document introducing generalized additive models.📈
Testing differences in cell type proportions from single-cell data.
Workshop on using Mixed Models with R
Demonstration of alternatives to lme4
Illustrate CR models with individual heterogeneity (multistate, random-effect, finite-mixture)
Using Fixed Effect, Random Effect and Hausman Taylor IV to estimate the impacts on wage
Comparative Social Research with Multi-level Modelling in R
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.
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
Connecting the Sustainable Development Goals with climate change and the energy transition
Project for the 2021/22 Advanced Econometrics class at the Faculty of Economic Sciences, University of Warsaw. In this project we build FE and RE panel data models to assess the relationship between firm performance and CEO gender.
Age-Gender-Country-Specific Death Rates Modelling and Forecasting: A Linear Mixed-Effects Model
Stata and R programs to automatically quasi-demean regressors following FGLS-RE or MLE-RE regression
The main aim of this code is to measure the co-movements along 9 different currencies.
Fit band-recovery models with temporal random effects