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# Everything to Know About Sample Size Determination

## A step-by-step interactive guide including common pitfalls

 Explore The Data Get The Deck

• Blinded Sample Size Re-estimation.nqt
• Blinded SiteAndSubject.nqt
• Center Covariate Reducing Sample Size.nqt
• Cluster Randomized Extension.nqt
• External Pilot Study Sample Size Example.nqt
• Log-Rank Test Everolimus.nqt
• Log-Rank Test with Dropout.nqt
• MaxCombo Model Selection with Delayed Effect.nqt
• Responder Analysis Higher Sample Size Chi-Squared.nqt
• Two Means Group Sequential Replication.nqt
• Two Proportions Inequality Difference Scale.nqt
• Two Proportions Inequality Ratio Scale.nqt
• Two Proportions Non-inferiority Difference Scale.nqt
• Two Proportions Non-inferiority Ratio Scale.nqt
• Two Sample t-test Simvastin.nqt
• Win Ratio for Composite Endpoint.nqt

## A step-by-step interactive guide including common pitfalls

Designing a trial involves considering and balancing a wide variety of clinical, logistical and statistical factors.

One decision out of many is how large a study needs to be to have a reasonable chance of success. Sample size determination is the process by which trialists can find the ideal number of participants to balance the statistical and practical aspects that inform study design.

In this interactive webinar, we provided a comprehensive overview of sample size determination, the key steps to successfully finding the appropriate sample size and cover several common pitfalls researchers fall into when finding the sample size for their study.

### In this free webinar we will cover

• What is sample size determination?

• A step-by-step guide to sample size determination

• Common sample size pitfalls and solutions

### Everything to Know About Sample Size Determination

In most clinical trials, sample size determination is found by reaching a predefined statistical power - typically defined as the Type II error or how likely a significant p-value is under a given treatment effect.

Power calculations require pre-study knowledge about the study design, statistical error rates, nuisance parameters (such as the variance) and effect size with each of these adding additional complexity.

Sample size determination has a number of common pitfalls which can lead to inappropriately small or large sample sizes with issues ranging from poor design decisions, misspecifying nuisance parameters or choosing the effect size inappropriately.

In this interactive webinar, we explore these and some solutions to avoid these mistakes and help maximise the efficiency of your clinical trial.

We provide a comprehensive overview of sample size determination, the key steps to successfully finding the appropriate sample size and cover several common pitfalls researchers fall into when finding the sample size for their study.

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