# 6a.11 - Summary

6a.11 - Summary

In 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.

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