Sentence examples for modeling after controlling from inspiring English sources

The longitudinal modeling after controlling for baseline values failed to show the whole trend slope to be different.

Then, we calculated odds ratio (OR) with 95% CI of abnormal biochemical function of the liver through multivariate modeling after controlling major risk factors, including age, gender, BMI, ethnic group, alcohol drinking, cigarette smoking, betel quid chewing and hepatitis B & C status.

The individual symptoms were modelled individually after controlling for age, sex (Model A) and adjustment for the 22 other symptoms in addition to age and sex (Model B).

Pleural invasion and tumor grade were not significant in this multivariate model, after controlling for other variables.

The levels of security needs and benevolence were also statistically important factors in all models, after controlling for gender, income and ideological preferences.

The effect was similar in direction and magnitude in the final model after controlling for additional antenatal factors (OR, 0.82; 95% CI, 0.65 to 1.04 P: =.1.04 P

Regression coefficients of these exposure biomarkers except bisphenol A remained significantly in the multiple regression models after controlling for age, sex, weight, smoking, and exercise for at least one of the two oxidative stress biomarkers (P < 0.05).

This result changes only slightly to 0.55 (0.13) in a DE model after controlling for smoking and BMI.

In a logistic regression model, after controlling for potential confounding by clinical and behavioural predictors of preterm delivery, unintended pregnancy was significantly associated with preterm delivery (adjusted RR = 1.82, 95% confidence interval [1.08,3.08], P = 0.026).

In the multivariate analysis, temporal trends in efficacy were assessed by using a Cox regression model after controlling for known risk factors such as age, parasitaemia at baseline, and mixed parasite infection.

Third, the associations between FISH markers and cancer status were assessed individually and in multiplicity models after controlling for clinical and biological parameters, such as smoking status and histology grade, using multiple logistic regression.