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An optimal modelling of predictors is crucial to achieve a clinically valid prediction model.
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In particular, we tested a model of predictors of binge drinking focusing on boredom proneness; we also examined the predictive and mediating role of drinking expectancies on binge drinking.
Logistic regression was used to build a multivariate model of predictors of PSA testing.
Table 6 shows that the multiple regression model of predictors of intention to leave.
Manual backward stepwise regression was used to develop a multivariable logistic regression model of predictors of delayed ANC in Rwanda.
The effect of the number of loci genotyped on outcome classification was investigated in a regression model of predictors of recrudescence within all recurrences.
DMARD Willingness and Patient Characteristics: Results of hierarchical linear regression modeling of predictors of DMARD willingness are presented in Tables 4 and 5.
An interaction term between log-distance and an indicator of wind direction was significant (p < 0.001) in regression models of predictors of NOx, NO2, and NO.
Risk Perception and Patient Characteristics: Results of hierarchical linear regression modeling of predictors of risk perception are presented in Tables 2 and 3.
In multivariate logistic regression models of predictors of death and poor functional outcome, the gelsolin levels on admission were an independent predictor.
We used an Akaike's Information Criterion (AIC -based selection criteriAIC -basede a final model of predictorselectionar incriteriayperuricemia.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com