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A Cox proportional hazards model was constructed to determine variables independently associated with hospital mortality.
Binary logistic regression modelling was used to determine variables predictive for focal therapy suitability.
Multivariate logistic regression models will be used to determine variables independently associated with the outcome variable.
Multivariate logistic regressions models will be used to determine variables independently associated with the outcome variable for questionnaire data.
Within regression models, a central issue is whether to use the full model incorporating all available variables or a reduced model determined by variable selection methods.
Table 2 Result of the logit model of factors determining cooperative membership Variables Coef.
We employed Hosmer and Lemeshow's model-building process to determine the variables that were associated with current smoking status (current smoker vs. former/never smoker) [ 27].
If the p-values for the Pearson chi-square and the likelihood ratio chi-square were < 0.05 then data were re tabulated using a goodness of fit model to determine if the response variable's profile differed significantly from the independent variable using the distribution ratios of the ≥ 65 group as the expected frequencies.
The Cox proportional hazard regression model was applied to determine independent variables and prognosis relative hazard.
The Cox regression model was applied to determine independent variables that may influence survival.
This conceptual model implies that demographic and socio-economic variables may determine all variables being studied.
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