Analyzing change in school psychology research

• Published in: Psychology in the schools Vol. 44; no. 5; pp. 535 - 542
• Main Authors: Kulikowich, Jonna M., Edwards, Maeghan N.
• Format: Journal Article
• Language: English
• Published: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.05.2007; John Wiley & Sons, Inc; Wiley
• Subjects: Antigen-antibody reactions, antigen-antibody complexes, antibody-complement and others. Study of affinity. Antigen presentation; Anxiety; Biological and medical sciences; Data Analysis; Fundamental and applied biological sciences. Psychology; Fundamental immunology; Hypothesis Testing; Individual Characteristics; Linear models; Molecular immunology; Performance Factors; Predictor Variables; Psychological Studies; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Psychometrics. Statistics. Methodology; Reading Achievement; School Psychologists; School Psychology; Social sciences research; Statistical analysis; Statistics. Mathematics; Stress Variables; Human; Statistical method; Academic achievement; Attentional disorder; Methodology; Hyperactivity; Anxiety disorder; School psychology; Linear model
• ISSN: 0033-3085; 1520-6807
• DOI: 10.1002/pits.20245

We look at three common research scenarios, one in the behavioral domain (i.e., disruptive behaviors) one in the cognitive domain (i.e., academic achievement), and one in the affective domain (i.e., anxiety and stress) for which school psychologists are asked to address important questions related to change. We list measurement and statistical considerations across these scenarios, including whether variables are manifest or latent, the scales of measurement, the dimensionality of measures, the units of analysis, the sample size, and the frequency or duration of time, given the primary nature of the variables under study. We suggest that researchers carefully consider whether assumptions can be met employing classical general linear models, or whether contemporary alternatives, such as hierarchical linear modeling (HLM), should be recommended for the more appropriate handling of data. © 2007 Wiley Periodicals, Inc. Psychol Schs 44: 535–542, 2007.