Ordinal logistic regression (ordered logistic regression) is a type of regression analysis that is used when the...
Data Science
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 is crucial for ensuring the...
In this blog post, I will show you how to use listcoef command in stata for logistic...
Logistic regression is commonly used to model a binary outcome (e.g. whether an individual accesses mental health services: Yes or No)....
Logistic regression is a statistical method for modeling binary outcomes, such as yes/no, success/failure, or alive/dead. It...
Regression diagnostics are crucial for validating the assumptions underlying linear regression models. One of the fundamental assumptions...
When reporting the results of a regression analysis, it is important to be careful about the language...
How it is different from Cronbach’s alpha? 📒 Dunn, T. J., Baguley, T., & Brunsden, V. (2014)....
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...
Beta coefficients and unstandardized coefficients are two different ways of presenting the results of regression analyses. Why...
In this post, I will show you how to run regressions with interaction effects using Stata, and...
In this blog post, I will show you how to run a continuous by continuous interaction in...
My steps to do quantitative research In this article, I will not talk about mathematics and formulas...
