PREP - Power & Sample Size PDF

**[Core Principles of Mental Health Research ]** **[PREP - Power & Sample Size ]** [Learning Outcomes:] - Explain the importance of sample size calculations - Define Type I and Type II errors - List the key factors which determine sample size and explain how they impact on the number...

**[Core Principles of Mental Health Research ]** **[PREP - Power & Sample Size ]** [Learning Outcomes:] - Explain the importance of sample size calculations - Define Type I and Type II errors - List the key factors which determine sample size and explain how they impact on the number of participants required for a study - Calculate sample sizes for simple studies with continuous and binary primary outcomes - Adjust sample sizes to account for loss to follow up [Approaches to Sample Size:] - Statistical/Scientific - How many patients are required to obtain reliable evidence of a treatment effect -- if it exists -- and to estimate any effect precisely - Economic/Pragmatic - How many patients are available? - How long will it take to recruit the required number? - How much will the study cost? - Ethical - How soon can a trial be stopped to avoid some patients getting an inferior treatment? - Credibility - If a trial is very small, it may be regarded as unreliable [Small Studies:] - Will not statistically detect clinically important, realistic, moderate sized treatment effects - Clinically significant, but not statistically significant - Produce imprecise estimates of effects - Wide confidence intervals for estimated difference - Findings less likely to be true in the population as a whole - More likely to result in publication bias - Small studies with p \< 0.05 are more likely to be submitted and accepted for publication than small studies with p \> 0.05 - Inconclusive and misleading for clinicians and researchers - Unethical for participants to spend time in a study that cannot deliver a robust result [Sample Size:] Too small: - Lack of precision - Real medical improvements unlikely to be distinguished from chance variation - Ethical considerations Too Large: - Waste of resources - Ethical considerations A well designed clinical trial will answer the research question with the smallest possible number of participants [Type I and Type II errors:] - Type I error: False Positive (i.e., there is an effect observed but no true effect in the population) (alpha) - Type II error: False Negative (i.e., there is no effect observed but there is an effect in the population) (Beta) - Power: 1-Beta