Why does sample size matter in program evaluation?

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Sample size matters in program evaluation for several reasons:
1. Statistical power.: A larger sample size increases the statistical power of the evaluation. Statistical power refers to the ability of a study to detect a true effect or relationship between variables.
2. Precision and accuracy.: A larger sample size leads to narrower confidence intervals around the estimates, providing greater precision and accuracy in estimating the true population parameters. This reduces the margin of error and increases the confidence in the findings.
3. Generalizability.: A larger sample size enhances the external validity or generalizability of the evaluation results. The findings are more likely to be representative of the larger target population, allowing for more confident conclusions and broader applicability of the results.
4. Robustness to attrition or missing data.: Attrition or missing data can occur in program evaluations, potentially introducing bias and reducing the effective sample size. A larger initial sample size helps mitigate the impact of attrition, providing more reliable results despite potential data loss.
5. Complex analysis.: Certain program evaluations involve complex statistical analyses, such as multivariate analysis or modeling. These analyses often require larger sample sizes to ensure reliable estimates and stable model fitting.