Sentence examples for by multiple regression with from inspiring English sources

The relationship between power of fMRI response and mean reaction time over all 11 working memory trials was explored by multiple regression, with age and mean reaction time to the control task as covariates, at voxel and regional levels of analysis.

The associations between exposure and outcome variables were then analyzed by multiple regression with adjustment for relevant covariates.

However, as described in research design and methods, the fenofibrate effect on (log-transformed) IAUCs was analyzed by multiple regression with fenofibrate, sex, (log-transformed) day of study fasting TG, and fenofibrate × TG interaction as independent variables.

C-peptide, proinsulin, blood glucose change, insulin dose, HbA1c and IDAA1c were analysed by multiple regression with age, sex, and antibody status (negative/positive) as explanatory variables in a compound symmetric repeated measurement model.

In established RA, analysis by multiple regression with correction for age, sex and disease duration revealed a significant association between TNF-RII genotype and the levels of sTNF-RI (P for trend = 0.01) and sTNF-RII (P for trend = 0.03) in the order TT > TG > GG.

In addition, the levels of sTNF-RI and sTNF-RII were significantly associated with TNF-RII genotype (P for trend = 0.02 and P for trend = 0.01, respectively) when the two populations were combined and analyzed by multiple regression with correction for age, sex and disease duration.

The skull BMD versus contaminant (∑PCB, ∑DDT, ∑CHL, HCB, ∑HCH, dieldrin, and ∑PBDE) relationships were explored by multiple regressions with skull BMD as the dependent variable and the age and contaminant concentrations as explanatory variables within age/sex groups (subadults of both sexes, adult females, and adult males).

The data for staff turnover and sick leave were analysed by multiple regression analyses with the independent variables of time, professions, units and interactions with time.

The potential confounding effects of age, body mass index (BMI), alcohol and coffee consumption, smoking and medicine use last month was evaluated by multiple regression analysis with stepwise entering the potential confounders one at the time.

* = calculations based on Tanner's references [ 8] Growth responses (annualized height velocities) during GH therapy were correlated, by multiple regression analysis, with potentially relevant variables as published before [ 14].

A unified suggestion, in which both A1C and insulin dose were included, was investigated by multiple regression analysis with the logarithm of stimulated C-peptide as the dependent variable and sex, age, A1C, and daily insulin dose (units per kilogram body weight) as independent variables 6 and 12 months after diagnosis.