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Key words were predict, screen, risk, score, [type two] diabetes, model, regression, risk assessment, risk factor, calculator, analysis, sensitivity and specificity, ROC and odds ratio.
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Risk ratio of death was calculated using the Cox regression risk model.
It may be appropriate to implement a rolling logistic regression risk model.
Regression risk modelling techniques perform best when there are relatively large numbers of events and comprehensive data for all biomarkers (Peduzzi et al, 1995).
Using the selected covariates, we constructed a multivariate unconditional logistic regression model for risk of TB.
Multivariate forward stepwise logistic regression model for risk factors predicting SWI was constructed.
Variables with p < 0.1 in bivariate analysis were incorporated into Logistic regression model for risk adjustment.
Using a multivariable logistic regression model, several risk factors for PRRSV infection were identified.
All correlations were below 0.8 and therefore could be entered into a regression model without risk of multi-colinearity.
Thereafter, all covariates mentioned above were entered in the regression model and risk ratios were mutually adjusted for all covariates.
Thereafter, all of these covariates were entered in the regression model and risk ratios were mutually adjusted for all covariates.
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