A Truly Multivariate Approach to Manova

Abstract

All too often researchers perform a Multivariate Analysis of Variance (MANOVA) on their data and then fail to fully recognize the true multivariate nature of their effects. The most common error is to follow the MANOVA with univariate analyses of the dependent variables. One reason for the occurrence of such errors is the lack of clear pedagogical materials for identifying and testing the multivariate effects from the analysis. The current paper consequently reviews the fundamental differences between MANOVA and univariate Analysis of Variance and then presents a coherent set of methods for plumbing the multivariate nature of a given data set. A completely worked example using genuine data is given along with estimates of effect sizes and confidence intervals, and an example results section following the technical writing style of the American Psychological Association is presented. A number of issues regarding the current methods are also discussed.

Mathematics Teachers’ Level of Knowledge and Practice on the Implementation of Higher-Order Thinking Skills (HOTS)

“…The MANOVA analysis in aggregate or overall (Multivariate Tests) used Pillai's Trace value as it was comprehensive and suitable for a different number of respondents for each category involving independent variable (Grice & Iwasaki, 2007). Meanwhile, the results of data analysis were also carried out separately (Tests of Between-Subjects Effects) as the researchers wanted to get more accurate results by using Bonferroni alpha value (0.05/8=0.00625).…”

“…Meanwhile, the results of data analysis were also carried out separately (Tests of Between-Subjects Effects) as the researchers wanted to get more accurate results by using Bonferroni alpha value (0.05/8=0.00625). According to Grice and Iwasaki (2007); An et al (2013), the use of Bonferroni can control the problem of Type 1 Error, which often occurs in a study. Table 2 shows a summary of the differences of each demographic factor on the dependent variables and described in detail by the researchers for each of the aspect.…”

The Relationship between Size and Performance of Palestinian Water Service Providers

“…MANOVA thus is to maximally discriminate between distinct groups of people, places, performance areas and things as. [17] [18] and [19].…”

Adaptability, Cognitive Flexibility, Personal Need for Structure, and Rigidity

“…Consequently, the authors followed Grice and Iwasaki (2007) and conducted a one-factor and between-subjects multivariate analysis of variance. This approach is interesting, because it allows us to understand how people differentiate at once on all eight dimensions combined instead of considering the dimensions one by one, or two at a time.…”