<ul><li>Researchers often observe patterns in binomial outcomes across ordinal predictors, but these patterns may arise due to random variation, necessitating robust statistical validation.</li><li>This essay explores the Cochran-Armitage trend test through a practical example of a clinical trial evaluating response rates across three dosage levels. The test’s mechanics, visualization techniques, and interpretation of results are demonstrated step-by-step.</li><li>The test identified an apparent upward trend in response rates as the dosage increased. However, the p-value of 0.1228 indicated that the trend was not statistically significant at the 0.05 threshold.</li><li>While visual patterns suggest a potential relationship, the Cochran-Armitage trend test underscores the importance of statistical rigor in trend validation. Further analysis with larger sample sizes or alternative methods may be required to confirm the observed pattern.</li></ul>

Unearthing Patterns in Ordered Data: The Power of the Cochran-Armitage Trend Test

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