0.12 13. multiple analysis of variance: part iii

About the Authors

• John R. Slate is a Professor at Sam Houston State University where he teaches Basic and Advanced Statistics courses, as well as professional writing, to doctoral students in Educational Leadership and Counseling. His research interests lie in the use of educational databases, both state and national, to reform school practices. To date, he has chaired and/or served over 100 doctoral student dissertation committees. Recently, Dr. Slate created a website ( Writing and Statistical Help ) to assist students and faculty with both statistical assistance and in editing/writing their dissertations/theses and manuscripts.
• Ana Rojas-LeBouef is a Literacy Specialist at the Reading Center at Sam Houston State University where she teaches developmental reading courses. Dr. LeBoeuf recently completed her doctoral degree in Reading, where she conducted a 16-year analysis of Texas statewide data regarding the achievement gap. Her research interests lie in examining the inequities in achievement among ethnic groups. Dr. Rojas-LeBouef also assists students and faculty in their writing and statistical needs on the Writing and Statistical Help website.

Now that you are in the SPSS output screen, your screen should look like the following: Your first table is titled Between-Subjects Factors and it is entirely redundant with the table immediately below it. The column of n in the Between-Subjects Factors table is duplicated in the Descriptive Statistics table. Therefore, we will not use the Between-Subjects Factors table.

Focusing on the Descriptive Statistics table will show you a column for the M , for the SD , and for the sample size, n . This information has been provided to you for each of the four dependent variables for each of the three groups. This information will be used in your Results section and should be kept.

Underneath the Descriptive Statistics table is the Box’s Test of Equality of Covariance Matrices. The information in this box involves checking one of the assumptions underlying use of a MANOVA procedure. The Sig. value in this box should be greater than .05 if the assumption is met. In the example below, the Sig. value is .234 which means that this particular assumption has been met. Readers should be informed whether the Box’s M assumption was met or was violated. See Field (2010) for a detailed explanation of Box’s M and the use of a MANOVA, even when this assumption is violated.

Underneath the Box’s Test of Equality of Covariance Matrices is the Multivariate Tests table. This table is important because it indicates whether or not a statistically significant difference is present among the reading groups (i.e., our independent variable) in the aggregated dependent variable (i.e., aggregated Verbal 1 through Verbal 4). For our purposes, we will use Wilks’ Lambda to determine whether or not a difference is present. In this example, a statistically significant difference is present.