Locally most powerful tests for detecting treatment effects when only a subset of patients can be expected to "respond" to treatment.
Two two-parameter models are developed for testing the hypothesis of no treatment effect against the alternative that a subset of the treated patients will show an improvement. To keep the range of measurements the same for treated and control patients, Lehmann alternatives are used in both models. Locally most powerful rank tests are developed for each model and each parameter. The asymptotic relative efficiency leads to a test that uses the scores s(i) = [i/(N + 1)]4. Two examples that support the usefulness of this nonparametric test are presented.
Conover
W J
WJ
Texas Tech University, Lubbock 79409.
Salsburg
D S
DS
D001219:Aspartate Aminotransferases / Q000378:metabolism; D003929:Diabetic Neuropathies / Q000188:drug therapy; D004358:Drug Therapy; D006333:Heart Failure / Q000188:drug therapy / Q000201:enzymology; D006801:Humans; D008954:Models, Biological; D011336:Probability; D011379:Prognosis; D011897:Random Allocation; D013223:Statistics as Topic; D014665:Vasodilator Agents / Q000627:therapeutic use
D014665:Vasodilator Agents; D001219:Aspartate Aminotransferases