You can use the t-test when you want to compare the means (averages) of continuous data between two groups, such as blood pressure or maximum concentration of a drug in urine (Cmax).
If you have data with a dichotomous outcome, you can use the Chi-Squared test instead - please try our Chi-Squared sample size calculator.
The calculator below will calculate the minimum sample size for you. Your expected effect size d is the standardised effect size according to Cohen’s definition. Cohen’s d is defined as the difference between the means of the two groups being compared, divided by the pooled standard deviation.
where Mi are the means of the two groups and Sp is the pooled standard deviation. You can use just the standardised Cohen's d value in this calculator, or alternatively you can enter the mean difference.You can estimate your expected effect size from the literature, such as past clinical trials.
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Multi-Arm & Multi-Stage (MAMS) Clinical Trials Design Tips The design of clinical trials is increasingly challenged by the Rising Costs, limited availability of eligible patient populations, and the growing demand for timely therapeutic evaluation. Traditional parallel-group designs, which typically compare a single intervention to a control, are often insufficient to meet these pressures in terms of speed, efficiency, and resource utilization.
You can use the Chi-Squared test to analyse your trial data or A/B test data if you have two groups with a dichotomous outcome. For example, you have two arms in your trial: the placebo and the intervention arm, and your endpoint is either yes or no, such as “did the subject experience an adverse event during the trial”. The calculator below will calculate the minimum sample size for you. Your expected effect size w is the standardised effect size according to Cohen’s definition.
How can you use the Clinical Trial Risk Tool to create a per-subject budget from a protocol or synopsis and a site Charge Master? The video below walks you through how the Clinical Trial Risk Tool by Fast Data Science can accelerate your budgeting. The Clinical Trial Risk Tool streamlines the creation of a per-subject budget by automating the typically manual process of extracting data from the Study Protocol and cross-referencing it with Charge Master/Fee Schedules.
