Sentence examples for for inclusion in the regression was from inspiring English sources

The selection of variables for inclusion in the regression was designed to account for key patient population characteristics (deprivation, proportion aged 65 or over, proportion who were white, proportion who were male), and characteristics of practices that reflect the systematic management of patients with chronic conditions.

The independent variables considered for inclusion in the regression model are listed in the first column of Table  1.

Potential confounders considered for inclusion in the regression models were age, sex, urinary creatinine, albumin, and body mass index (BMI).

Potential confounders considered for inclusion in the regression models were age, sex, urinary creatinine, body mass index (BMI), and total uAs.

The variables chosen for inclusion in the regression analyses were those significantly correlated with the RDQ score and AUCG based on correlational analysis.

Variables in the bivariate analysis were considered eligible for inclusion in the regression modeling if they were significant at p ≤ 0.10, or if prior evidence or theoretical considerations supported their inclusion.

Collinearity was assessed by generating a correlation coefficient matrix for all variables to be considered for inclusion in the regression model.

A P value of 0.05 was required for inclusion in the regression analysis.

Epidemiological and clinical significance of the variables was considered for inclusion in the regression model.

Instead, country of birth was coded for inclusion in the regression as 1) born in Mexico or 2) born elsewhere.

Measures related to quality of life were assessed for inclusion in the regression models.