Sentence examples for models that controlled from inspiring English sources

In regression models that controlled for confounders, which included very low birth weight, magnesium remained a significant risk factor (adjusted odds ratio, 3.7; 95% CI, 1.1-11.9; P =.03).

Since there could be multiple passengers in the same vehicle, the SAS GLIMMIX procedure (SAS Institute Inc 2014) with random effects was used to generate odds ratios with 95%% confidence intervals using multilevel models that controlled for violation of the assumption of independence associated with multiple rear-seated occupants in the same vehicle.

In a series of logistic regression models that controlled for age, gender, disease duration, β-interferon use, and depression, migraine in MS patients was significantly associated (p < 0.01) with trigeminal and occipital neuralgia, facial pain, Lhermitte's sign, temporomandibular joint pain, non-headache pain and a past history of depression.

Nevertheless, logistic regression models that controlled for the 10 most statistically significant Class II SNPs, as well as the 8 Class III SNPs identified in this study, demonstrated an independent allelic contribution of rs4959039 to MS susceptibility.

Odds ratios are from random effects regression models that controlled for the number of hospitalizations.

p-values are from mixed effects logistic regression models that controlled for the number of hospitalizations.

They are far less complex than most of PHY models that control the same amount of communication parameters.

Conventional software engineering approaches and even standard languages compose web services as workflow models that control the business logic required to coordinate data over participating services.

The final step was to divert brain signals to a computer model that controlled the movements of a robot.

An additional advantage was a multivariable approach in the logistic modeling that controlled for multiple other factors including psychiatric co-morbidities.

SF-36 domain scores were placed into a logistic regression model that controlled for significant demographic variables (gender, educational level, perceived health).