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Risk Perception and Patient Characteristics: Results of hierarchical linear regression modeling of predictors of risk perception are presented in Tables  2 and 3.

Data on one or more key variables were missing from N=71 patients and these were excluded from the modeling of predictors which therefore included 107 participants.

DMARD Willingness and Patient Characteristics: Results of hierarchical linear regression modeling of predictors of DMARD willingness are presented in Tables  4 and 5.

Multivariable modeling of predictors associated with the presence of adjustment for clustering showed a strong and significant association between any type of clustering adjustment and inclusion of an epidemiologist/clinical trials methodologist on the study team.

Multivariable modeling of predictors associated with adjustment for clustering showed a strong and significant association between any type of clustering adjustment and inclusion of an epidemiologist/clinical trials methodologist on the study team.

Similar(55)

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.

An optimal modelling of predictors is crucial to achieve a clinically valid prediction model.

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.

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