Sentence examples for using separate linear regression from inspiring English sources

Score differences in EQ-5D utility and EQ-VAS scores were examined using separate linear regression models, with and without adjustment for variables potentially influencing HRQoL (listed above).

Initially, associations between socioeconomic position and the novel CHD risk factors were investigated using separate linear regression models for socioeconomic position during childhood (aged 4), early adulthood (aged 26) and middle age (aged 53).

For the region of interest analyses, groups were compared using separate linear regressions for each outcome measure, in each region of interest.

Because of previous research indicating potentially susceptible subgroups [ 10, 15], we examined effect modification of the association between 28 day exposure to BC and HRV parameters by obesity (defined as BMI ≥ 30 kg/m; yes/no), hypertension (yes/no), diabetes (yes/no) and oxidative stress allelic profile (high/low; dichotomized based on median score) using separated linear regression models.

First, we used separate linear regression analyses to test for associations between maternal and paternal smoking during pregnancy and child ADHD symptoms.

We used separate linear regression models to estimate associations between BMI z-scores and WC (as dependent variables) and individual or grouped PAHs categorized according to quartiles (based on the weighted distributions in the study population).

We will use separate linear regression models to determine if, at 1-month and 7-month time points, ERP mean amplitudes, reach precision, and Bayley motor scores differ by intervention group in our CP participants.

We used separate linear regression models to examine the association between a doctor's summary scores and a range of characteristics of the doctor, and of their patient and colleague samples one model for patient scores, the other for colleague scores.

Matched measurements of SpO2 (limited to values ≤ 98%) and PaO2 from patients admitted with acute respiratory distress syndrome were used to determine the relationship between S/F and P/F, using three separate linear regression models, for patients on <8 cmH2O PEEP, 8 12 cmH2O PEEP and >12 cmH2O PEEP.

Specifically, we regressed daily concentrations of each PM2.5 constituent on total PM2.5 concentrations using a separate linear regression model for each time period to generate a constituent residual for each daily concentration value of the constituent.

To distinguish between the roles of the two types of codon usage preferences (tRNA optimization and increased G+C), we first isolated the relationships of GFP genes' CAI with G+C content and, separately, with bacterial fitness, using two separate linear regressions, and then examined the relationship between the residual variations in fitness and the G+C contents.