Related Experiment Video
Updated: Aug 14, 2026

Advancing Dyslexia Assessment in Children Through Computerized Testing
Published on: August 16, 2024
Non-inferiority trials: the 'at least as good as' criterion with dichotomous data
Larry L Laster1, Mary F Johnson, Mitchell L Kotler
1School of Veterinary Medicine, University of Pennsylvania, 3900 Delancey St., Philadelphia, PA 19104, USA. larryl@vet.upenn.edu
Abstract:
The 'at least as good as' criterion, introduced by Laster and Johnson for a continuous response variate, is developed here for applications with dichotomous data. This approach is adaptive in nature, as the margin of non-inferiority is not taken as a fixed difference; it varies as a function of the positive control response. When the non-inferiority margin is referenced as a high fraction of the positive control response, the procedure is seen to be uniformly more efficient than the fixed margin approach, yielding smaller sample sizes when sizing non-inferiority trials under identically specified conditions. Extending this method to proportions is straightforward, but highlights special considerations in the design of non-inferiority trials versus superiority trials, including potential trade-offs in statistical efficiency and interpretability.
Related Concept Videos
Test for Homogeneity
Testing a Claim about Standard Deviation
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Goodness-of-Fit Test
Types of Hypothesis Testing
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p ≠ 0.5.
Expected Frequencies in Goodness-of-Fit Tests
Ordinal Level of Measurement
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the...

