Logistic regression is commonly used to model a binary outcome (e.g. whether an individual accesses mental health services: Yes or No)....
Stata
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...
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...
Running a bivariate regression can help us understand the relationship between two variables. In this tutorial, we’ll...
Handling missing data is an essential part of any data analysis. Multiple imputation is a robust method...
Two way plot line is a tool for visualizing the relationship between two variables in Stata. It...
Correlation analysis is a statistical technique that measures the strength and direction of the relationship between two...
The chi-square test is an analysis used when both the independent and dependent variables are categorical variables....
T-test is a statistical method that compares the means of two groups or samples. It can be...
