InData Science CollectivebyFabio Sigrist·Jun 24Quantile Regression with Mixed-Effects Models in Python and RScalable quantile regression with grouped random effects using GPBoost
Sae-Hwan Park·Jun 20, 2025Inside Mixed Effect ModelWhen your neural network treats every hospital the same, but your statistician intuition screams that they shouldn’t beA response icon2A response icon2
Donghyeok Lee·Jun 8, 2025How to Model Random Effects: A Statistical and Predictive PerspectiveWhen you first learn statistics, you usually start with the basics of regression:
vinay shukla·May 30, 2025Untangling the Threads: A Deep Dive into Linear Mixed ModelsUnlocking Insights from Nested Data: A Guide to Linear Mixed Models
Jacob Mazurkiewicz·Aug 15, 2024Fixed Effect vs Random Effect ANOVAs (There’s a Difference)When we’re first introduced to the Analysis of Variance test in introductory statistics classes, we usually assume that the formulas given…
InData Analytics MasterybyNilimesh Halder, PhD·Apr 18, 2024Mastering Random Effects Models: A Comprehensive Statistical Guide with Python ApplicationsArticle Outline
Eunbee Chu·Feb 28, 2024Credit Card Company — Random Effects and Hierarchical Linear Models & Bayesian EstimationIntroduction
Karen Grace-Martin·Feb 7, 2024The Difference Between Random Factors and Random EffectsMixed models are hard.A response icon1A response icon1
Shivangi Choudhary·Dec 26, 2023Causal Inference techniques for Panel Data in Retail — Part IIHello readers! In my previous article on Comprehensive Guide on Causal Inference in Retail — Part I , I discussed about the assumptions …
InTDS ArchivebyFabio Sigrist·Jul 11, 2023Mixed Effects Machine Learning for High-Cardinality Categorical Variables — Part II: GPBoost…A demo of GPBoost in Python & R using real-world dataA response icon1A response icon1
