# 6a.11 - Summary

6a.11 - SummaryIn this lesson, among other things, we learned to:

- Identify studies for which sample size is an important issue
- Estimate the sample size required for a confidence interval for p for given \(\delta\) and \(\alpha\), using normal approximation and Fisher's exact methods
- Estimate the sample size required for a confidence interval for μ for given \(\delta\) and \(\alpha\), using normal approximation when the sample size is relatively large
- Estimate the sample size required for a test of \(H_0 \colon \mu_1 = \mu_2\) to have \((1 - \beta)\%\) power for given \(\delta\) and \(\alpha\), using normal approximation, with equal or unequal allocation.
- Estimate the sample size required for a test of \(H_0 \colon p_1 = p_2\) for given \(\delta\) and \(\alpha\) and \(\beta\), using normal approximation and Fisher’s exact methods
- Use a SAS program to estimate the number of events required for a logrank comparison of two hazard functions to have \((1 - \beta)\%\) power with given \(\alpha\)
- Use Poisson probability methods to determine the cohort size required to have a certain probability of detecting a rare event that occurs at a \(\text{rate} = \xi\).
- Adjust sample size requirements to account for multiple comparisons and the anticipated noncompliance rates.