Identifying Atypical Change at the Individual Level from Childhood to Adolescence

Autor/inn/en	Estrada, Eduardo; Ferrer, Emilio; Shaywitz, Bennett A.; Holahan, John M.; Shaywitz, Sally E.
Titel	Identifying Atypical Change at the Individual Level from Childhood to Adolescence
Quelle	In: Developmental Psychology, 54 (2018) 11, S.2193-2206 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Estrada, Eduardo)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0012-1649
DOI	10.1037/dev0000583
Schlagwörter	Change; Children; Adolescents; Age Differences; Verbal Ability; Individual Development; Intelligence Tests; Identification; Statistical Analysis; Longitudinal Studies; Dyslexia; Grade 1; Grade 3; Grade 5; Grade 7; Grade 9; Connecticut; Wechsler Intelligence Scale for Children + Suchen Sie Ihr Suchwort? Wandel; Child; Kind; Kinder; Adolescent; Adolescence; Adoleszenz; Jugend; Jugendalter; Jugendlicher; Age; Difference; Age difference; Altersunterschied; Mündliche Leistung; Individuelle Entwicklung; Intelligence test; Intelligenztest; Identifikation; Identifizierung; Statistische Analyse; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Dyslexics; Legasthenie; Lese-Rechtschreib-Schwäche; School year 01; 1. Schuljahr; Schuljahr 01; School year 03; 3. Schuljahr; Schuljahr 03; School year 05; 5. Schuljahr; Schuljahr 05; School year 07; 7. Schuljahr; Schuljahr 07; School year 09; 9. Schuljahr; Schuljahr 09
Abstract	Identifying change at the individual level is an important goal for researchers, educators, and clinicians. We present a set of statistical procedures for identifying individuals who depart from a normative change. Using Latent Change Scores models (LCS), we illustrate how the Individual Likelihood computed from a statistical model for change ("IL") and from an alternative unrestricted model ("ILsat") can be used to identify atypical trajectories in situations with several measurement occasions. Using LCS and linear regression, we also show how the observed and latent change residuals can be used to identify atypical individual change between 2 measurement occasions. We apply these methods to a measure of general verbal ability (from WISC-R), from a large sample of individuals assessed every 2 years from Grade 1 to 9. We demonstrate the efficiency of these techniques, illustrate their use to identify individual change in longitudinal data, and discuss potential applications in developmental research. (As Provided).
Anmerkungen	American Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01