Sentence examples for multivariable model use from inspiring English sources

An increased risk of subsequent diabetes mellitus has been associated previously with total body irradiation, abdominal irradiation, cranial irradiation (though not after adjustment in a multivariable model), use of alkylating agents, and younger age at diagnosis (Meacham et al, 2009).

Cost estimates for intent, firearm type, and payer source were obtained from the multivariable model using the BYLEVEL option in conjunction with the LSMEANS statement.

We built a multivariable model using log binomial regression for possible explanation, adjusting for biologic and known confounding factors for racial association with disease and health conditions.

We refit the multivariable model using a dichotomous indicator for the DCIS risk groups.

Re-estimating the main multivariable model using a subset of 'severe' complaints produced very similar results to the main model.

Explanatory variables with a p value < 0.25 were included in the multivariable model using a stepwise descending method (backward).

All the variables studies and VPI score were entered to build a multivariable model using covariance analysis (ANCOVA).

Variables that were significant in the univariate analysis were included in the multivariable model using a forward-selection strategy.

Five of these six statistically significant predictors remained in the final multivariable model using the step-wise backwards-elimination procedure.

Variables, which were associated with the outcome (p<0.10) using Wald tests for trend, were entered into a multivariable model using a forward stepwise model selection strategy.

Covariates with p ≤ 0.10 from an exact conditional score test in univariable models were examined together in a multivariable model using the stepwise selection method.