Single-case and Small-n Experimental Designs (ePub)
It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal...
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This practical guide explains the use of randomization tests and provides example designs and macros for implementation in IBM SPSS and Excel.
It reviews the theory and practice of single-case and small-n designs so readers can draw valid causal inferences from small-scale clinical studies.
The macros and example data are provided on the book's website so that users can run analyses of the text data as well as data from their own studies.
Ideal as a text for graduate-level courses on single-case, small-n design, and/or randomization tests, this inexpensive book also serves as a supplement in statistics or research methods courses. Practitioners and researchers with an applied clinical focus also appreciate this book's accessible approach.
Pat Dugard taught statistics at the University of Abertay Dundee until 1999 and has also taught courses at the Open University. She now concentrates on writing. She received her PGDip in Mathematical Statistics from the University of Cambridge.
Portia File is a psychologist and computer scientist experienced in teaching university courses on research methods. She taught at University of Abertay Dundee from 1983 until 2007. She received her PhD in Cognitive Psychology from the University of Texas at Austin in 1975.
Jonathan Todman is a Clinical Psychologist in the Pain Management Programme at NHS Greater Glasgow and Clyde in Glasgow, Scotland. He received his Clinical Psychology Doctorate from Edinburgh in 2010.
- Autoren: Pat Dugard , Portia File , Jonathan Todman
- 2012, 2. Auflage, 304 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1136588477
- ISBN-13: 9781136588471
- Erscheinungsdatum: 27.04.2012
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: ePub
- Größe: 9.69 MB
- Mit Kopierschutz
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