Sentence examples for multivariable linear model from inspiring English sources

Multiple statistical comparisons were performed using ANOVA in a multivariable linear model.

Significant variables in the univariate analyses were entered as potentially prognostic variables into a backward, stepwise selection procedure to construct a multivariable linear model that provides a natural logarithm transformed prediction of LOS (ln [LOS]).

The multivariable linear model determined to find predictors for the SDSCA-G sum score had a R of 0.043 and was based on a sample size of N = 253.

* Significantly different (p < 0.05) between groups in a multivariable linear model with age and gender as cofactors Quality of care was defined based on concepts of structure, process, and outcome [ 22, 23], and the interpretation of the outcome data discriminated between intervention- and process-related items of care [ 24, 25].

We accounted for differences in patient characteristics and admission diagnoses between physicians by estimating a patient level multivariable linear model of total hospital charges during the hospital stay as a function of patient age, sex, race, diagnosis related group, indicator variables for Charlson-Deyo comorbid conditions, and year and physician indicators.

Previous efforts on this topic were based on multivariable linear models.

Multivariable linear modelling with L1/L2 penalised regression was used to identify the miRNAs which showed the greatest predictive ability for each hallmark signature summary score across the cancer types considered, thereby identifying those miRNAs common to the gene signature across tumour types (see Methods and Fig. 1b).

Making use of this analysis, multivariable linear models with one-, three-,hree-, and four-variables that can accurately predict CH4 uptake of MOFs at room temperature and pressures ranging from 1 to 65 bar were developed.

Multivariable linear models were used to assess survivor occupational differences by cancer- and treatment-related variables.

Next, bivariate linear models were used to estimate the crude association between each predictor and the negative consequences of substance use, and multivariable linear models were used to estimate the independent effect of each predictor controlling for the remaining variables.

Associations between maternal genetic variants and both child cognition and LC-PUFA levels and ratios in colostrum were assessed using multivariable linear models and evaluated using likelihood ratio tests.