Propensity score matching (PSM) is a statistical technique that allows us to estimate the effect of a...
Stata
Aspect Fixed Effects (FE) Random Effects (RE) Definition Represent constant parameters that apply to all individuals in the sample. Capture variation across...
Understanding Fixed Effects, Random Effects, and Mixed Effects 1) Fixed Effects Models: In fixed effects models, the...
This post covers Poisson regression models using the HINTS 6 dataset. Our dependent variable (DV) is drinkdaysperweek,...
Regression Coefficients, Odds Ratios, and Marginal Effects Feature Regression Coefficients Odds Ratios Marginal Effects Definition Represents the...
Ordinal logistic regression (ordered logistic regression) is a type of regression analysis that is used when the...
Multinomial logistic regression is a method for modeling categorical outcomes with more than two levels. It allows...
In statistical analysis, particularly in regression models, identifying outliers and high-leverage observations matters for the accuracy and...
In this blog post, I will show you how to use listcoef command in stata for logistic...
Logistic regression is a statistical method for modeling binary outcomes, such as yes/no, success/failure, or alive/dead. It...
Ordinary Least Squares (OLS) and Maximum Likelihood Estimation (MLE) are two ways to estimate relationships between variables...
Regression diagnostics are what validate the assumptions underlying linear regression models. One of the fundamental assumptions is...
Differences from Cronbach’s alpha 📒 Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to...
Before we can trust the results of a regression model, we need to make sure that some...
In this blog post, I will show you how to compare the fit of different regression models...
