Automated multiple regression model-building techniques often hide important aspects of data from the data analyst. Such features as nonlinearity, collinearity, outliers, and points with high leverage ...

(2) The main patterns in the plant distribution are adequately described by multiple regression models using transformations of aspect and slope values. Aspect and slope are obviously related to ...

Outcomes in acute optic neuritis tend to be worse at 6 months for men, patients who are older and those with poorer ...

Lasso-Cox analysis uses the “glmnet” R software package to integrate survival time, survival state, and gene expression data to screen and identify candidate ARGs for constructing prognostic models to ...

Learn how ARIMA models use time series data for accurate short-term forecasting. Discover its pros, cons, and essential tips for financial predictions.

Multiple regression models forecast a variable using a linear combination of predictors, whereas autoregressive models use a combination of past values of the variable.

Regression Analysis When intending to uncover cause and effect, statisticians rely on regression analysis. This mathematical model uses past data to quantify the relationships among variables.

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 ...