Linear Models

Linear Models

How to Perform ANCOVA Using Linear Models (with R Examples)

ANCOVA (analysis of covariance) is a widely used statistical method for comparing the mean values of multiple groups on a continuous outcome while adjusting for the influence of a related continuous variable. ANCOVA extends ANOVA (analysis of variance) by integrating a continuous independent variable into the model to minimize bias and control for potential confounding

Linear Models

How to Create and Interpret Q–Q Plots (From Scratch in R)

In this Statistics Note, we learn how to create Q-Q plots from the scratch in R. A quantile-quantile plot (Q-Q plot for short) is a scatter plot that shows how one empirical distribution approximates a theoretical distribution. Before we dive into QQ plots, let’s clarify an important concept: quantiles. What is a quantile? A quantile

Linear Models

Regression Residuals for Total Energy Intake Adjustment

Confounders are undesirable variables that affect the relationship between two variables of interest in a study. For example, in epidemiological research studying the effects of a nutrient on a health issue, such as diabetes, the participant’s body size or physical activity can confound the relationship between the nutrient and the health issue. Therefore, it is

Scroll to Top