New in power and sample size
- Contingency tables
- Stratified 2×2 tables (Cochran–Mantel–Haenszel)
- 1:M matched case–control studies
- Trend in J×2 tables (Cochran–Armitage)
- Survival analysis
- 2-sample log-rank test
- 2-sample exponential test
- Cox PH regression
- Multiple values of parameters
- Automatic and custom tables and graphs
With Stata's power, you can compute power, sample size, and effect size. Enter any two and get the third.
Among other new features, power now provides power and sample size for matched case–control studies.
For instance, consider cancer among smokers and nonsmokers. How many case–control pairs do we need to achieve 80% power of detecting a 1.7 odds ratio with a 5% significance test if we used a 2-sided association test? If we knew from previous studies that the probability of exposure (smoking) for controls was roughly 0.22, we would type
. power mcc .22, oratio(1.7)
and learn that we need 285 cases and 285 controls.
1:M matching is often used to reduce the required number of cases because cases are often more difficult to obtain than controls. It is thus useful to evaluate designs with different values of M.
We could plot power curves for designs with 1:1, 1:2, 1:3, and 1:4 matching by typing
. power mcc 0.22, oratio(1.7) n(200(10)300) m(1 2 3 4) graph
Upgrade now Order Stata Read even more about power analysis for survival analysis and contingency tables in our Stata 14 announcement.