Sentence examples for determinants in the final model from inspiring English sources
The logistic regression technique allowed us to calculate the risk of ASF seropositivity as a function of the determinants in the final model using the formula: Prevalence (seropositive) = 1/1 + e-[α + Season*β1 + Source*β2 + Herdsize*β3 + Season*Herdsize*β4].
It was also the most significant determinant in the final model for waist-height ratio, a marker of central adiposity, overall neonatal adiposity as determined by SS + TR and sum of skinfolds, independent of maternal BMI, neonatal gender, total gestational age, maternal education or study group assignment.
However, co-morbidities and disease stage were included in our analyses and age remained a determinant in the final models.
As a consequence, in the multivariate analysis it is to some extent arbitrary which specific work-related determinant was included in the final model.
As a preceding step to selecting our models, logistic regression models were fitted in a systematic order by controlling for different sets of covariates so as to identify the set of determinants to be controlled for in the final model.
Logistic regression was used to estimate the independent effects of each determinant with the final model including variates based on all determinants of interest.
All determinants below the 0.10 significance level in the multivariate analyses were retained in the final model for heritability estimation.
They were all kept in the final model as they were independent and highly significant determinants of outcome (P<0.01).
Covariables are included in the final model only if they modify the regression coefficient of ward care model (i.e. the central determinant) by more than 10% (regardless of statistical significance of effects).
