Sample size requirements for the internal validation of psychiatric scales

• Published in: International journal of methods in psychiatric research Vol. 20; no. 4; pp. 235 - 249
• Main Authors: Rouquette, Alexandra, Falissard, Bruno
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.12.2011; John Wiley & Sons, Inc; Wiley
• Subjects: Bioinformatics; Computer Science; Data processing; Databases, Factual; Databases, Factual - statistics & numerical data; Factor analysis; Factor Analysis, Statistical; Female; Human health and pathology; Humans; Life Sciences; Literature reviews; Male; Mental Disorders; Mental Disorders - diagnosis; Principal components analysis; Psychiatric Status Rating Scales; Psychiatric Status Rating Scales - standards; Psychiatrics and mental health; Psychiatry; Quantitative Methods; questionnaires; Reproducibility of Results; Retrospective Studies; Sample Size; validation studies; questionnaires; factor analysis; validation studies; psychiatry; Sample size
• ISSN: 1049-8931; 1557-0657; 1557-0657; 1234-988X
• DOI: 10.1002/mpr.352

The ratio of subjects to variables (N/p), as a rule to calculate the sample size required in internal validity studies on measurement scales, has been recommended without any strict theoretical or empirical basis being provided. The purpose of the present study was to develop a tool to determine sample size for these studies in the field of psychiatry. First, a literature review was carried out to identify the distinctive features of psychiatric scales. Then, two simulation methods were developed to generate data according to: (1) the model for factor structure derived from the literature review and (2) a real dataset. This enabled the study of the quality of solutions obtained from principal component analysis or Exploratory Factor Analysis (EFA) on various sample sizes. Lastly, the influence of sample size on the precision of Cronbach's alpha coefficient was examined. The N/p ratio rule is not upheld by this study: short scales do not allow smaller sample size. As a rule of thumb, if one's aim is to reveal the factor structure, a minimum of 300 subjects is generally acceptable but should be increased when the number of factors within the scale is large, when EFA is used and when the number of items is small. Copyright © 2011 John Wiley & Sons, Ltd.