Statistical Power Clause Samples
The Statistical Power clause defines the minimum probability that a study or analysis will detect an effect if one truly exists. In practice, this clause typically requires that research or testing methodologies are designed to achieve a specified statistical power level, such as 80% or 90%, ensuring that the sample size and study design are adequate. Its core function is to ensure the reliability and validity of study results by minimizing the risk of false negatives, thereby supporting sound decision-making based on the data collected.
Statistical Power. The study had 51% statistical power to detect an absolute difference of 30 percentage points between the PVI and IC groups’ rates of virologic suppression at a 5% significance level for a two-sided test. Comparing the IC and PC arms, the study had 67% power to detect the same difference. We used logistic regression to estimate the unadjusted and adjusted impact of the IC treatment relative to the PVI arm and relative to the PC arm. The predictor variables included treatment arm indicators and the stratifying variable. Our hypothesis tests were constructed relying on the asymptotic normality of the maximum likelihood estimator, but we obtained similar results when we conducted permutation tests. All statistical procedures were implemented using Stata 13 (StataCorp, College Station, TX, USA). Supplementary analyses indicate that the three arms had similar demographic and clinical characteristics at baseline, although individuals in the PC arm were older (median age 48.93 years) than individuals in the IC arm (median 40.10) and PVI arm (median 42.88). Individuals in the IC arm had higher pVL values leading up to the enrollment visit relative to individuals in the other arms. The PC arm had a higher rate of missing pVL measurements at the fifth study visit compared to the other arms. In the IC arm, 48% of participants had at least one suppressed viral load measurement across the three visits prior to the enrollment visit. The percentage was 43% in the PVI arm and 36% in the PC arm. Thus, many individuals in the study had experienced some previous success in achieving viral suppression, although some individuals in the study had faced much more difficulty achieving success in the past.
Statistical Power. This study is a pilot investigation intended to estimate effect sizes of the safety and efficacy of MDMA-assisted psychotherapy in people with PTSD. Because of their exploratory nature, pilot studies are often underpowered for detecting the desired effect. Because it is a pilot study in a small sample, statistical power is difficult to assess but it is likely to be low. Analyses of MAPS’ completed US study of MDMA-assisted psychotherapy in 20 people with PTSD found an effect size of 1.24 for treatment efficacy, as represented by changes in CAPS score [77]. The estimated effect size for this study may be lower as a result of comparing the full dose of MDMA with a comparator dose of MDMA instead of with inactive placebo. The sponsor intends to combine effect size estimates to develop a dose response curve as a meta-analyses of CAPS scores across MAPS-sponsored pilot studies. The sponsor used Java applications created by ▇▇▇▇▇ and posted on the website listed below to calculate estimated statistical power for this study, assuming an effect size of 0.75 for the impact of two sessions of MDMA-assisted psychotherapy on symptoms [169], reducing the effect size to account for the hypothesized effects of using a comparator dose. The software calculated an estimated power of 0.21, indicating an underpowered study. Had we used the higher effect size of 1.1, power analysis still indicates that this study is underpowered, with an estimated effect size of 0.37. Statistical power estimates were not available for secondary and exploratory measures, as they were previously not used in sponsor-supported studies.
Statistical Power. This is a pilot study intended to collect estimates of effect size of Full dose (125mg) MDMA compared to Low dose (40mg)