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Consumption change data were pooled in random effects models and meta-regression was used to explore predictors of change.
Linear regression analysis was used to explore predictors of CD127 in a multivariate setting.
Stepwise-logistic regression was used to explore predictors of Khat dependence.
Logistic regression was used to explore predictors of AVF FTM in the Belfast cohort.
Logistic regression was also used to explore predictors of being overdue for screening.
Linear regression was used to explore predictors of SUDI risk scores.
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Stepwise linear regression analysis was used to explore clinical predictors of memory outcome after surgery (excluding brain volumetric predictors): including age at onset of epilepsy, duration of epilepsy, lesion type (DNT or hippocampal sclerosis), current seizure status and medicated versus medication-free.
Food supplementation experiments have long been used to explore whether predictors of fitness such as condition [1] and productivity [2], or population parameters such as survival [3] and recruitment [4], depend upon food availability.
Univariate and multi-variable Cox proportional hazards models were used to explore potential predictors of TRM.
Binary logistic regression was used to explore potential predictors of autopsy.
A regression model was used to explore the predictors of long-term care utilization after hospital discharge.
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