Cluster Randomization Studies Have Become More Common In Place of Traditional Trials That
Randomly Assign Participants One at a Time When This Method Is Impractical For Theoretical, Ethical, Or
Practical Reasons. In the Setting of a Complementary Poison Model With Potentially Misclassified Data, We
Evaluate Three Interval Estimators For Binomial Misclassification Rates: One Based on the Wald Statistic,
Another on the Score Statistic, and a Third on the Profile Log-Likelihood Statistic. As a Result of Its
Improved Power and Lower Type I Error, the Redesigned Test Comes Highly Recommended. Semiparametric
Testing of Misclassification Estimates Information on the Parameters Employed In G (X*, Z) That Underlie
Parametric Models, Misclassification, and Model and Identification-Related Problems