InData Science + AI at MicrosoftbyJuhi Singh·Jul 1, 2025Causal inference in practice: Methodological lessons from DoWhy, Fixed Effects, and EconMLBy Juhi Singh, Bonnie Ao, Nehal Jain, and Sebastian Antinome
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 …
InData Science + AI at MicrosoftbyCeren Altincekic·Oct 18, 2022Reducing omitted variable bias with fixed effects regression modelsLinear model solutions for when you suspect time-invariant confounders in your panel dataA response icon1A response icon1
InTDS ArchivebySachin Date·Jun 13, 2022What Are Dummy Variables and How to Use Them in a Regression ModelAnd how to interpret the regression coefficients of dummy variablesA response icon1A response icon1
Harsh·Dec 21, 2021Random Effects ModelLinear regression is a mathematical approach to model the relationship between a scalar dependent variable (also called response variable)…
InDev GeniusbyDr. Marc Jacobs·Sep 28, 2021Randomness in Mixed ModelsAll statistical models have at least one systematic and one random part. In ANOVA or Generalized Linear Models (GLM), the systematic part…
Marco Laube·Sep 8, 2021The paired t-test and linear mixed modelsThere are many methods for the analysis of data with multiple levels. However, there is still significant confusion about how these methods…
Luis Garcia Fuentes·Sep 3, 2021Practical econometrics; Difference-in-differences — Multiple groups and periods in Python (Fixed…A refresher, explanation, and the python code. No derivation! Somewhat technical but if you read the title and understood it, you are…A response icon4A response icon4
Soumak Basumallik·Feb 15, 2021Over-Specified and Under-Specified Correlation Structures: A Simulation Case-Study using SASThe purpose of this project is to investigate what happens to the estimation of fixed effect parameters, the standard error estimates of…
