1. Logistic Regression Bandit Thinkhamrop, PhD. (Statistics) Department of Biostatistics and Demography Faculty of Public Health, Khon Kaen University

2. Begin at the conclusion 7

3. Type of the study outcome: Key for selecting appropriate statistical methods Study outcomeStudy outcome Dependent variable or response variableDependent variable or response variable Focus on primary study outcome if there are moreFocus on primary study outcome if there are more Type of the study outcomeType of the study outcome ContinuousContinuous Categorical (dichotomous, polytomous, ordinal)Categorical (dichotomous, polytomous, ordinal) Numerical (Poisson) countNumerical (Poisson) count Event-free durationEvent-free duration

4. The outcome determine statistics Continuous CategoricalCountSurvival Mean Median Proportion (Prevalence Or Risk) Rate per “space” Median survival Risk of events at T (t) Linear Reg.Logistic Reg.Poisson Reg.Cox Reg.

5. Statistics quantify errors for judgments Parameter estimation [95%CI] Hypothesis testing [P-value] Parameter estimation [95%CI] Hypothesis testing [P-value]

6. Back to the conclusion Continuous CategoricalCountSurvival Magnitude of effect 95% CI P-value Magnitude of effect 95% CI P-value Mean Median Proportion (Prevalence or Risk) Rate per “space” Median survival Risk of events at T (t) Answer the research question based on lower or upper limit of the CI Appropriate statistical methods

7. Begin at the wrong destination

9. Forest plot

10. Another “wrong scale” forest plot

11. Receiver Operating Characteristic Cure

12. Optimal cut-off point

13. Diagnostic performance