By George A. Milliken, Dallas E. Johnson
A best-selling reference for 17 years, research of Messy information: quantity 1 has now been greatly revised and taken completely modern. The authors have streamlined the presentation and integrated a couple of fresh advancements within the box, together with advances in random results versions and refinements to a number of comparability strategies. most significantly, they've got thoroughly up-to-date fabric related to software program and aspect how SAS-Mixed, SAS-GLM, and different applications can be utilized to enhance scan layout and version research. effortless to learn with stable examples and a comfy format, this version will surely take its position as a favourite reference of test designers and statisticians.
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Additional info for Analysis of messy data
4 Brown and Forsythe’s Test Brown and Forsythe (1974) used Levene’s process and modified it by doing a one-way analysis of variance on the absolute values of the deviations of the observations from the median of each treatment. The absolute values of the deviations from the medians are given by uij = |yij - yi med|, i = 1, 2, º , t; j = 1, 2, º , ni. The F-test from the analysis of variance provides a test of the equality of the treatment means of the absolute values of the deviations. If the means are different, then there is evidence that the deviations for one treatment are on the average larger than the deviations for another treatment.
Conover et al. and Olejnik and Algina discuss some nonparametric tests, but they are more difficult to calculate and the above recommended tests perform almost as well. An example follows where each of the tests for equality of variances is demonstrated. 1 are from a paired-association learning task experiment performed on subjects under the influence of two possible drugs. Group 1 is a control group (no drug), group 2 was given drug 1, group 3 was given drug 2, and group 4 was given both drugs.
2) Can pairwise comparisons among the means be made? t 3) Can a test of the hypothesis of the form Âi=1 ci mi = a be tested and can confidence t intervals be constructed about Âi=1 ci mi? In addition, there are also questions about the variances that may be of interest, such as 1) Are all of the variances equal? 2) Are there groupings of the treatments where within a group the variances are equal and between groups the variances are not equal? Before questions about the means of the model can be answered, an appropriate description of the variances of the treatments must be obtained.