Sentence examples for multivariable models controlling from inspiring English sources

Exact(4)

This effect was reversed (1.25, 1.14 to 1.37) in the multivariable models controlling for a history of self harm.

In multivariable models controlling for age, gender, body habitus, strength, and comorbid illnesses, AMD subjects reported greater fear of falling as compared to controls (β = -0.77 logits, 95% CI = -1.5 to -0.002, p = 0.045).

In multivariable models, controlling for age, race, marital status, income, education, height, alcohol use, clinic site, and smoking, we again observed no association with fasting glucose but a trend toward increased insulin and HOMA-IR with higher categories of parity (Ptrend = 0.01 for insulin and 0.02 for HOMA-IR).

Multivariable models controlling for sex, age at diagnosis, marital status, race, current steroid use and smoking did not significantly change the mean score difference between fatigued and nonfatigued CD or UC patients for the mental health or physical health component scores.

Similar(56)

The multivariable models controlled for age (continuous) sex, history of hypertension, smoking ever, never) body mass index, alcohol consumption, serum total cholesterol level and family history of severe headache.

Initial multivariable models controlled for age and race.

To determine whether waiting times explained associations of age and ethnic groups, region of residence and deprivation quintile with excess mortality, the EHRs from multivariable models (controlled for all other covariables) were compared with models without waiting times.

The multivariable models controlled for age (continuous), sex, history of hypertension (yes, no), smoking (ever, never), body mass index (<25, 25 to 29, ≥30 weight (kg)/(height (m)), alcohol consumption (0, 1-19, 20-39, ≥40 g/day), serum total cholesterol level (continuous), and family history of severe headache (yes, no).

With the exception of education, these risk estimates changed little following individual adjustment for other covariates and in the multivariable model controlling simultaneously for all covariates except education.

In a multivariable model controlling for some potential confounders, including illness severity, hyperoxia had an odds ratio for hospital death of 1.2 (95% CI, 1.1 to 1.6).

This association persisted in a multivariable model controlling multiple prognostic factors, including the presence and sites of extrathoracic disease (HR 1.24; P=0.01.24

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