The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection ...

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...

This article describes a polynomial growth curve quantile regression model that provides a comprehensive assessment about the treatment effects on the changes of the distribution of outcomes over time ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Many of Pew Research Center’s survey analyses show relationships between two ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

I was composing a long reply in the original thread and it got somewhat unwieldy, so let’s move things over here: Q. Is there any way to see how the regression changes have effected the prediction at ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...