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Dose response curves and 95% confidence intervals for oral and intranasal routes of exposure were derived using logistic models (logit and probit).
The probabilities of continuing were derived using logistic regression.
The previously developed score was derived using logistic regression, assigning points to each of the predictive findings included in the model according to the strength and direction of the association with smear negative TB [17], and optimal cut-off points were identified with ROC analysis.
A combined score was derived using logistic regression and predicted probabilities.
Odds ratios (ORs) of advanced stage at diagnosis adjusted for patient and tumour characteristics were derived using logistic regression.
A combined prognostic score using both NLR and mGPS was then derived using logistic regression to determine the predicted probability of death.
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The strength of associations between HLA class I alleles and viral polymorphisms in the "total" cohort, "high CD4" group or "low CD4" group was derived using a logistic regression model that corrected for phylogeny, and is reported as a log2-adjusted odds ratio.
The final model was derived using forward logistic regression.
All estimates of risk are presented as odds ratios, derived using conditional logistic regression modelling.
Univariable predictors of AHFS were derived using binary logistic regression analysis.
Odds ratios and 95% confidence intervals (CIs) were derived using unconditional logistic regression models.
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