Unit 4: Contingency Tables & Simple Logistic Regression: Inference in Case CC and QC
Contingency Table Methods for Binary Outcomes
- Apply contingency tables for binary outcomes with binary or multi-level predictors
- Identify the appropriate conditional percentages to compare to answer specific research questions.
- Conduct the appropriate chi-square test for association or when appropriate use Fisher’s exact test.
- Calculate and interpret measures of association for binary outcomes
- Excess Risk (or Risk Difference)
- Relative Risk
- Odds Ratio
- Discuss issues related to the three measures of association for binary outcomes.
Logistic Regression using One Predictor
- Use LOG rules for powers and division appropriately as needed to work with logistic models.
- Discuss the reasons the logistic model is preferred for modeling probabilities.
- Discuss the benefit of the logistic model that it can be rewritten in terms of a linear model using an appropriate LOGIT transformation.
- Use the logistic model to predict probabilities or LOG-ODDS.
- State the assumptions of the logistic regression model.
- Derive and appropriately interpret the log-odds-ratio and odds-ratio for comparing levels of a categorical predictor to the reference group.
- Derive and appropriately interpret the log-odds-ratio and odds-ratio for a one-unit increase or a c-unit increase for a continuous predictor.
- Appropriately use SAS output to conduct logistic regression analysis for one predictor and multiple predictors, possibly including interactions.
- Construct confidence intervals for parameter estimates and odd-ratios by hand for comparisons to a reference group for categorical predictors.
- Construct confidence intervals for parameter estimates and odd-ratios by hand for a one-unit or c-unit increase in a continuous predictor.
- Be able to find odd-ratio and confidence intervals in the reverse direction of comparisons given in software output by taking the reciprocal of the values in the output.
- Use contrast and oddsratio statements to test and estimate complex comparisons.
- Appropriately use percent increase or percent decrease interpretations for odd-ratios.
The following lessons from Penn State STAT 501 are linked in the materials as support materials for Unit 4. Our videos will be the primary instruction for Unit 4 and Unit 5.