Abstract
Multiple pairwise comparison tests of treatment means are of great interest in applied research. Two modifications for the Tukey test were proposed. The power of unilateral and bilateral Student, Waller-Duncan, Duncan, SNK, REGWF, REGWQ, Tukey, Bonferroni, Sidak, unilateral Dunnet statistical tests and the modified tests, Sidak, Bonferroni 1 and 2, Tukey 1 and 2, has been compared using the Monte Carlo method. Data were generated for 600 experiments with eight treatments in a randomized block design, of which 400 had four and 200 eight blocks. The differences between the treatment means in relation to the control were 30%, 20%, 15%, 10%, 5%. Two extra treatments did not differ from the control. A coefficient of variation of 10% and a probability Type I error of α = 0.05 were adopted. The power of all the tests decreased when the differences to the control, decreased. The unilateral and bilateral Student t, Waller-Duncan and Duncan tests showed greater number of significative differences, followed by unilateral Dunnett, modified Sidak, modified Bonferroni 1 and 2, modified Tukey 1, SNK, REGWF, REGWQ, modified Tukey 2, Tukey, Sidak and Bonferroni. There is great loss of efficiency for all tests in relation to the unilateral Student t test for each difference of the treatment to the control, when the differences between means decrease. The modified tests were always more efficient than their original ones.
Highlights
In applied research the evaluation of the hypothesis under investigation can be obtained developing experiments in which different treatments are included
Results are generally submitted to statistical analysis of variance, testing a global null hypothesis H using the F test and comparing the means by mul
The unilateral Student test was somewhat more powerful than the bilateral Student t test followed by the Waller-Duncan; Duncan, Dunnett unilateral, siM, BM, BM, TuM, SNK, REGWF, REGWQ, TuM, Tukey, Sidak and Bonferroni tests
Summary
In applied research the evaluation of the hypothesis under investigation can be obtained developing experiments in which different treatments are included. Results are generally submitted to statistical analysis of variance, testing a global null hypothesis H using the F test and comparing the means by mul-. (Piracicaba, Braz.), v.65, n.4, p.428-432, July/August 2008 tiple comparison procedures (Hochberg & Tamhane, 1987; Hsu, 1996). A common practice is to compare new treatments to a control. In corn or wheat breeding, for example, new cultivars have to be compared to the main cultivar. New feeding treatments have to be compared to a main treatment that is in use. New promising medicines have to be compared to the one adopted, before FDA in USA or ANVISA in Brazil give permission for their commercialization
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
