Sentence examples for Regression models with multiple predictors from inspiring English sources

For each of the 11 influenza seasons, we applied negative binomial regression models with multiple predictors to relate the weekly IPP rates with the indicators of influenza and RSV activities while adjusting for the weekly mean temperature, total sunshine, and total precipitation.

Thus, we constructed two multiple binomial logistic regression models with only three predictor variables in each model, including serum SP levels in both models.

In particular, in this multiple regression model with seven predictors, the time spent on assessment and DCV had significant positive regression weights.

Taking into account the way regression coefficients in a multiple regression model with two predictors are calculated, it is easy to show that the parameters in the means models should generally also differ across zygosity.

Women with a history of endometriosis had an increased risk of developing ovarian or endometrial cancer when all other predictors were also considered (Table  2).> -wrap-foot> bodybody mass index aORs were estimated using a multiple logistic regression model, with the predictors listed in the first column of the table bAge was used as a nonlinear continuous predictor.

The multiple regression model with all ten predictors produced R = .351.351

Figure 1 shows the scatterplot of the log-transformed maternal serum PCBs against the residuals of the log thymic index from a multiple linear regression model with all predictor variables except PCBs.

Adjusted multiple ordered logistic regression models with dummy variables for ethnicity explored predictors for IFG/IGT and diabetes.

These components were used in subsequent analysis as predictors in three separate multiple regression models with PDT, SDT and TDT as outcome variables (table 3).

In multiple regression models with each component of calcium intake included, breast-milk intake was the most significant predictor of weight and length (P=0.0004 and P=0.004, respectively).

To identify possible predictors of low fibrinogen concentration we fitted two multiple linear regression models with fibrinogen concentration as the dependent variable.