Sentence examples for multivariable linear models from inspiring English sources
Previous efforts on this topic were based on multivariable linear models.
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.
From multivariable linear models, several significant associations were found between sociodemographic factors and CogState measures.
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).
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.
Two multivariable linear regression models (separate models for each outcome) were used to examine the simultaneous association between all predictor variables and outcomes).
