Statistical Methods for Categorical and Time-to-Event Outcomes
Methodological Approaches for Categorical and Time-to-Event Outcomes »
1. Estimation of Single-Group Proportions and Confidence Intervals
- Method 1: Statistical methods for proportion estimation and confidence interval calculation
- Implementation of 10 validated statistical methods for proportion estimation
2. Calculation of Effect Measures from 2×2 Contingency Tables
- Statistical methods for analyzing 2×2 contingency table data
- Estimation of odds ratios, risk ratios, and risk differences with corresponding standard errors and confidence intervals
3. Transformation Between Different Effect Measures
3.1 Conversion Between Odds Ratio and Risk Ratio
- Scenario 1: Event rate (P) in the non-exposed group is known.
- Scenario 2: Event rate (P) in the non-exposed group is unknown, but P > 10%.
- Scenario 3: Event rate (P) in the non-exposed group is unknown, but P < 10%
3.2 Conversion Between Hazard Ratio and Risk Ratio
- Scenario 1: Follow-up time is short or event rate is low.
- Scenario 2: Event rate in the control group is known at the end of the follow-up period.
- Scenario 3: Event rate is unknown, but the rates of both groups are estimated between [0.2, 0.8].
- Scenario 4: Event rate is unknown, but event rates of both groups are estimated between [w, u].
4. Advanced Statistical Methods
4.1 Calculation of Number Needed to Treat
- Method 1: Estimation of number needed to treat from various effect measures
- Method 2: Calculation of confidence intervals for number needed to treat
4.2 E-Value Calculation
- Method 1: Calculation of E-value for unmeasured confounding assessment
- Method 2: Estimation of E-value for sensitivity analysis
5. Other Types
5.1 Switch Reference Group
- If a study reports a relative comparison of A vs. B, while a meta-analysis requires the effect for B vs. A.