What sample sizes for reliability and validity studies in neurology?

Jeremy C. Hobart*, Stefan J. Cano, Thomas T. Warner, Alan J. Thompson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Rating scales are increasingly used in neurologic research and trials. A key question relating to their use across the range of neurologic diseases, both common and rare, is what sample sizes provide meaningful estimates of reliability and validity. Here, we address two questions: (1) to what extent does sample size influence the stability of reliability and validity estimates; and (2) to what extent does sample size influence the inferences made from reliability and validity testing? We examined data from two studies. In Study 1, we retrospectively reduced the total sample randomly and nonrandomly by decrements of approximately 50 % to generate sub-samples from n = 713-20. In Study 2, we prospectively generated sub-samples from n = 20-320, by entry time into study. In all samples we estimated reliability (internal consistency, item total correlations, test-retest) and validity (within scale correlations, convergent and discriminant construct validity). Reliability estimates were stable in magnitude and interpretation in all sub-samples of both studies. Validity estimates were stable in samples of n ≥ 80, for 75 % of scales in samples of n = 40, and for 50 % of scales in samples of n = 20. In this study, sample sizes of a minimum of 20 for reliability and 80 for validity provided estimates highly representative of the main study samples. These findings should be considered provisional and more work is needed to determine if these estimates are generalisable, consistent, and useful.
Original languageEnglish
Pages (from-to)2681-2694
Number of pages0
JournalJ Neurol
Volume259
Issue number12
DOIs
Publication statusPublished - Dec 2012

Keywords

  • Adult
  • Aged
  • Female
  • Humans
  • Male
  • Middle Aged
  • Multiple Sclerosis
  • Neurology
  • Prospective Studies
  • Reproducibility of Results
  • Retrospective Studies
  • Sample Size

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