Variables measured in medicine are usually continuous, such as blood pressure, serum
glucose, and drug dosage. There are statistical methods to confirm whether these variables …

In a previous article in this series, we explained correlation analysis which describes the
strength of relationship between two continuous variables. In this article, we deal with linear …

While regression models have become standard tools in medical research, understanding
how to properly apply the models and interpret the results is often challenging for beginners …

Although regression models play a central role in the analysis of medical research projects,
there still exist many misconceptions on various aspects of modeling leading to faulty …

Logistic regression analysis is a statistical technique to evaluate the relationship between
various predictor variables (either categorical or continuous) and an outcome which is …

Background Regression analysis is an important statistical method for the analysis of
medical data. It enables the identification and characterization of relationships among …

Multi-stage regression analysis and path analysis provide important complements to the
traditional regression analysis. Although regression (covariance) analysis is a useful and …

Sažetak Logistic regression is used to obtain odds ratio in the presence of more than one
explanatory variable. The procedure is quite similar to multiple linear regression, with the …

In medical research, when independent variables are categorical (ie, dividing groups),
statistical analysis is often required. This situation mostly occurs on randomized controlled …

Statistics are used in medicine for data description and inference. Inferential statistics are
used to answer questions about the data, to test hypotheses (formulating the alternative or …