Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

One of the most promising avenues of research in computer-assisted language learning is the potential for language learners to make use of language corpora. However, using a corpus requires use of a corpus tool as an interface, typically a concordancer. How such a tool can be made most accessible to learners is an important issue. Specifically,…

Specific language impairment (SLI) comprises impairments in receptive and/or expressive language. Aim of this study was to evaluate a screening for SLI. 61 children with SLI (SLI-children, age-range 4-6 years) and 61 matched typically developing controls were tested for receptive language ability (Token Test-TT) and for intelligence (Wechsler…

The current study investigated how the five components of planned happenstance skills are related to vocational identity statuses. For determination of relationships, cluster and discriminant analyses were conducted sequentially on a sample of 515 university students in South Korea. Cluster analysis revealed vocational identity statuses to be…

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent…

Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused…

In this article, the authors investigated the relations of students' perceptions of teachers' oral feedback with teacher expectancies and student self-concept. A sample of 1,598 Taiwanese children in Grades 3 to 6 completed measures of student perceptions of teacher oral feedback and school self-concept. Homeroom teachers identified students for…

The validity of the Differential Ability Scales (DAS) was assessed among children with attention-deficit/hyperactivity disorder (ADHD) and a matched control sample. The sample included 45 children with ADHD (69% with comorbidity) and 45 controls matched by age, gender, ethnicity, and parental educational level. Multivariate analysis of variance…

Correlation matrices and standard deviations are the building blocks of many of the commonly conducted analyses in published research, and AERA and APA reporting standards recommend their inclusion when reporting research results. The authors argue that the inclusion of correlation/covariance matrices, standard deviations, and means can enhance…

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…

The available methods for analyzing and interpreting data with multivariate analysis of variance are reviewed, and guidelines for their use are presented. Causal models that underlie the various methods are presented to facilitate the use and understanding of the methods. (Author/PN)

Describes the method of discriminant analysis, including the concept of discriminant function, discriminant score, group centroid, and discriminant weights and loadings. Discusses methods for testing the statistical significance of a function, methods of using the function in classification, and the concept of rotating functions. Illustrates the…

Discusses three topics related to interpretation of discriminant analyses (DA's): (1) partial F ratios and partial Wilks's lambdas for predictor variables in standard, step-down, and stepwise DA's; (2) relation of goals of classification to definition/evaluation of classification rules; and (3) significance tests for total hit rates in internal…

Standardization procedures in discriminant analysis are discussed. Three leading software packages--SPSSX, BMDP, and SAS--are compared in terms of their calculations of unstandardized and standardized discriminant coefficients. Estimation procedures are described for each. Arguments are presented for within-group, rather than total, variance…