Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
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Updated
May 19, 2025 - Python
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
Mixed-effect model to test differences in cell type proportions from single-cell data, in R
A document introducing generalized additive models.📈
An R package for extracting results from mixed models that are easy to use and viable for presentation.
👓 Functions related to R visualizations
Mixed models @lme4 + custom covariances + parameter constraints
Workshop on using Mixed Models with R
Functions for using mgcv for mixed models. 📈
Demonstration of alternatives to lme4
Using Fixed Effect, Random Effect and Hausman Taylor IV to estimate the impacts on wage
Illustrate CR models with individual heterogeneity (multistate, random-effect, finite-mixture)
An R package for I-prior regression
a meta-analysis on the effect of intravenous magnesium on myocardial infarction
Connecting the Sustainable Development Goals with climate change and the energy transition
Content of the course "Regression and Statistical Models (52571)" at The Hebrew University of Jerusalem, in the Department of Statistics and Data Science.
Copula Based Bivariate Beta-Binomial Model for Diagnostic Test Accuracy Studies
Raw files for a document providing an overview of mixed models from varying perspectives.
Stata and R programs to automatically quasi-demean regressors following FGLS-RE or MLE-RE regression
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