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Published in: Journal of Neurology 12/2012

01-12-2012 | Original Communication

What sample sizes for reliability and validity studies in neurology?

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

Published in: Journal of Neurology | Issue 12/2012

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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.
Literature
1.
go back to reference Zajicek J, Fox P, Sanders H et al (2009) Cannabinoids for treatment of spasticity and other symptoms related to multiple sclerosis (CAMS study): multi-centre randomised placebo-controlled trial. Lancet 362:1517–1526CrossRef Zajicek J, Fox P, Sanders H et al (2009) Cannabinoids for treatment of spasticity and other symptoms related to multiple sclerosis (CAMS study): multi-centre randomised placebo-controlled trial. Lancet 362:1517–1526CrossRef
2.
go back to reference Lees K, Zivin J, Ashwood T et al (2006) NXY-059 for acute ischemic stroke. N Engl J Med 354:588–600PubMedCrossRef Lees K, Zivin J, Ashwood T et al (2006) NXY-059 for acute ischemic stroke. N Engl J Med 354:588–600PubMedCrossRef
3.
go back to reference Hobart J, Cano S, Zajicek J, Thompson A (2007) Rating scales as outcome measures for clinical trials in neurology: problems, solutions, and recommendations. Lancet Neurol 6:1094–1105PubMedCrossRef Hobart J, Cano S, Zajicek J, Thompson A (2007) Rating scales as outcome measures for clinical trials in neurology: problems, solutions, and recommendations. Lancet Neurol 6:1094–1105PubMedCrossRef
4.
go back to reference Darzi A (2008) High quality care for all: NHS Next Stage Review final report. Department of Health, London Darzi A (2008) High quality care for all: NHS Next Stage Review final report. Department of Health, London
5.
go back to reference UK Department of Health (2010) Equity and excellence: liberating the NHS. Her Majesty’s Stationery Office, London UK Department of Health (2010) Equity and excellence: liberating the NHS. Her Majesty’s Stationery Office, London
8.
go back to reference McDowell I, Jenkinson C (1996) Development standards for health measures. J Health Serv Res Policy 1:238–246PubMed McDowell I, Jenkinson C (1996) Development standards for health measures. J Health Serv Res Policy 1:238–246PubMed
9.
go back to reference Fitzpatrick R, Davey C, Buxton MJ, Jones DR (1998). Evaluating patient-based outcome measures for use in clinical trials. Health Technol Assess 2:1–86 Fitzpatrick R, Davey C, Buxton MJ, Jones DR (1998). Evaluating patient-based outcome measures for use in clinical trials. Health Technol Assess 2:1–86
10.
go back to reference Scientific Advisory Committee of the Medical Outcomes Trust (2002) Assessing health status and quality of life instruments: attributes and review criteria. Qual Life Res 11:193–205CrossRef Scientific Advisory Committee of the Medical Outcomes Trust (2002) Assessing health status and quality of life instruments: attributes and review criteria. Qual Life Res 11:193–205CrossRef
11.
go back to reference Feldt L, Woodruff D, Sailh F (1987) Statistical inference for coefficient alpha. Appl Psychol Measure 11:93–103CrossRef Feldt L, Woodruff D, Sailh F (1987) Statistical inference for coefficient alpha. Appl Psychol Measure 11:93–103CrossRef
12.
13.
go back to reference DeVellis RF (1991) Scale development: theory and applications. Sage publications, London DeVellis RF (1991) Scale development: theory and applications. Sage publications, London
14.
go back to reference Rea L, Parker R (1992) Designing and conducting survey research: a comprehensive guide. Jossey-Bass, San Fransisco Rea L, Parker R (1992) Designing and conducting survey research: a comprehensive guide. Jossey-Bass, San Fransisco
15.
go back to reference Ferguson E, Cox T (1993) Exploratory factor analysis: a user’s guide. Int J Select Assess 1:84–94CrossRef Ferguson E, Cox T (1993) Exploratory factor analysis: a user’s guide. Int J Select Assess 1:84–94CrossRef
16.
go back to reference Nunnally JC, Bernstein IH (1994) Psychometric theory, 3rd edn. McGraw-Hill, New York Nunnally JC, Bernstein IH (1994) Psychometric theory, 3rd edn. McGraw-Hill, New York
17.
go back to reference Eliasziw M, Young S, Woodbury M, Fryday-Field K (1994) Statistical methodology for the concurrent assessment of interrater and interrater reliability: using goniometric measurements as an example. Phys Therapy 74:777–788 Eliasziw M, Young S, Woodbury M, Fryday-Field K (1994) Statistical methodology for the concurrent assessment of interrater and interrater reliability: using goniometric measurements as an example. Phys Therapy 74:777–788
18.
go back to reference Streiner DL, Norman GR (1995) Health measurement scales: a practical guide to their development and use, 2nd edn. Oxford University Press, Oxford Streiner DL, Norman GR (1995) Health measurement scales: a practical guide to their development and use, 2nd edn. Oxford University Press, Oxford
19.
go back to reference Cantor AB (1996) Sample-size calculations for Cohen’s Kappa. Psych Methods 1:150–153CrossRef Cantor AB (1996) Sample-size calculations for Cohen’s Kappa. Psych Methods 1:150–153CrossRef
20.
go back to reference Ware JE, Harris WJ, Gandek B, Rogers BW, Reese PR (1997) MAP-R for windows: multitrait/multi-item analysis program—revised user’s guide. Health Assessment Lab, Boston Ware JE, Harris WJ, Gandek B, Rogers BW, Reese PR (1997) MAP-R for windows: multitrait/multi-item analysis program—revised user’s guide. Health Assessment Lab, Boston
21.
go back to reference Feldt L, Ankenmann R (1998) Appropriate sample size for a test of equality of alpha coefficients. Appl Psychol Measure 22:170–178CrossRef Feldt L, Ankenmann R (1998) Appropriate sample size for a test of equality of alpha coefficients. Appl Psychol Measure 22:170–178CrossRef
22.
go back to reference Feldt L, Ankenmann R (1999) Determining sample size for a test of equality of alpha coefficients when the number of part-tests is small. Psychol Methods 4:366–377CrossRef Feldt L, Ankenmann R (1999) Determining sample size for a test of equality of alpha coefficients when the number of part-tests is small. Psychol Methods 4:366–377CrossRef
23.
go back to reference Cocchetti D (1999) Sample size requirements for increasing the precision of reliability estimates: problems and proposed solutions. J Clin Exper Neuropsychol 21:567–570CrossRef Cocchetti D (1999) Sample size requirements for increasing the precision of reliability estimates: problems and proposed solutions. J Clin Exper Neuropsychol 21:567–570CrossRef
24.
go back to reference Charter R (1999) Sample size requirements for precise estimates of reliability, generalizability, and validity coefficients. J Clin Exper Neuropsychol 21:559–566CrossRef Charter R (1999) Sample size requirements for precise estimates of reliability, generalizability, and validity coefficients. J Clin Exper Neuropsychol 21:559–566CrossRef
25.
go back to reference MacCallum R, Widaman K, Zhang S, Hong S (1999) Sample size in factor analysis. Psychol Methods 4:84–99CrossRef MacCallum R, Widaman K, Zhang S, Hong S (1999) Sample size in factor analysis. Psychol Methods 4:84–99CrossRef
26.
go back to reference Mendoza J, Stafford K, Stauffer J (2000) Large-sample confidence intervals for validity and reliability coefficients. Psychol Methods 5:356–369PubMedCrossRef Mendoza J, Stafford K, Stauffer J (2000) Large-sample confidence intervals for validity and reliability coefficients. Psychol Methods 5:356–369PubMedCrossRef
27.
go back to reference Perkins D, Wyatt R, Bartko J (2000) Penny-wise and pound-foolish: the impact of measurement error on sample size requirements in clinical trials. Biol Psychiatr 47:762–766CrossRef Perkins D, Wyatt R, Bartko J (2000) Penny-wise and pound-foolish: the impact of measurement error on sample size requirements in clinical trials. Biol Psychiatr 47:762–766CrossRef
28.
go back to reference Bonett D (2002) Sample size requirements for testing and estimating coefficient alpha. J Educ Behav Stat 27:335–340CrossRef Bonett D (2002) Sample size requirements for testing and estimating coefficient alpha. J Educ Behav Stat 27:335–340CrossRef
29.
go back to reference Maydeu-Olivares A, Coffman D, Hartman W (2007) Asymptotically distribution-free (ADF) interval estimation of coefficient alpha. Psychol Methods 12:157–176PubMedCrossRef Maydeu-Olivares A, Coffman D, Hartman W (2007) Asymptotically distribution-free (ADF) interval estimation of coefficient alpha. Psychol Methods 12:157–176PubMedCrossRef
30.
go back to reference Bonett D (2002) Sample size requirements for estimating intraclass correlations with desired precision. Stat Med 21:1331–1335PubMedCrossRef Bonett D (2002) Sample size requirements for estimating intraclass correlations with desired precision. Stat Med 21:1331–1335PubMedCrossRef
31.
go back to reference Barrett P, Kline P (1981) The observation to variable ratio in factor analysis. Personality Study Group Behav 1:23–33 Barrett P, Kline P (1981) The observation to variable ratio in factor analysis. Personality Study Group Behav 1:23–33
32.
go back to reference Hobart JC, Lamping DL, Fitzpatrick R, Riazi A, Thompson AJ (2001) The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain 124:962–973PubMedCrossRef Hobart JC, Lamping DL, Fitzpatrick R, Riazi A, Thompson AJ (2001) The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. Brain 124:962–973PubMedCrossRef
33.
go back to reference Cano SJ, Warner TT, Linacre JM et al (2004) Capturing the true burden of dystonia on patients: the cervical dystonia impact profile (CDIP-58). Neurology 63:1629–1633PubMedCrossRef Cano SJ, Warner TT, Linacre JM et al (2004) Capturing the true burden of dystonia on patients: the cervical dystonia impact profile (CDIP-58). Neurology 63:1629–1633PubMedCrossRef
34.
go back to reference Ware JE, Sherbourne DC (1992) The MOS 36-Item Short-Form Health Survey (SF-36): I. Conceptual framework and item selection. Med Care 30:473–483PubMedCrossRef Ware JE, Sherbourne DC (1992) The MOS 36-Item Short-Form Health Survey (SF-36): I. Conceptual framework and item selection. Med Care 30:473–483PubMedCrossRef
35.
go back to reference Cella DF, Dineen K, Arnason B et al. (1996) Validation of the functional assessment of multiple sclerosis quality of life instrument. Neurology 47:129–139PubMedCrossRef Cella DF, Dineen K, Arnason B et al. (1996) Validation of the functional assessment of multiple sclerosis quality of life instrument. Neurology 47:129–139PubMedCrossRef
36.
go back to reference EuroQoL Group (1990) EuroQoL: a new facility for the measurement of health-related quality of life. Health Policy 16:199–208CrossRef EuroQoL Group (1990) EuroQoL: a new facility for the measurement of health-related quality of life. Health Policy 16:199–208CrossRef
37.
go back to reference Goldberg DP, Hillier VF (1979) A scaled version of the General Health Questionnaire. Psychol Medicine 9:139–145CrossRef Goldberg DP, Hillier VF (1979) A scaled version of the General Health Questionnaire. Psychol Medicine 9:139–145CrossRef
38.
go back to reference Gompertz P, Pound P, Ebrahim S (1994) A postal version of the Barthel Index. Clin Rehabil 8:233–239CrossRef Gompertz P, Pound P, Ebrahim S (1994) A postal version of the Barthel Index. Clin Rehabil 8:233–239CrossRef
39.
go back to reference Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. Acta Psychiatr Scand 67:361–370PubMedCrossRef Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. Acta Psychiatr Scand 67:361–370PubMedCrossRef
40.
go back to reference Cronbach LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16:297–334 Cronbach LJ (1951) Coefficient alpha and the internal structure of tests. Psychometrika 16:297–334
41.
go back to reference Nunnally JC (1978) Psychometric theory, 2nd edn. McGraw-Hill, New York Nunnally JC (1978) Psychometric theory, 2nd edn. McGraw-Hill, New York
42.
go back to reference Eisen M, Ware JE, Donald CA, Brook RH (1979) Measuring components of children’s health status. Med Care 17:902–921PubMedCrossRef Eisen M, Ware JE, Donald CA, Brook RH (1979) Measuring components of children’s health status. Med Care 17:902–921PubMedCrossRef
44.
go back to reference Green S, Lissitz R, Mulaik S (1977) Limitations of coefficient alpha as an index of test unidimensionality. Educ Psychol Measure 37:827–838CrossRef Green S, Lissitz R, Mulaik S (1977) Limitations of coefficient alpha as an index of test unidimensionality. Educ Psychol Measure 37:827–838CrossRef
45.
go back to reference McGraw KO, Wong SP (1996) Forming inferences about some intraclass correlation coefficients. Psychol Methods 1:30–46CrossRef McGraw KO, Wong SP (1996) Forming inferences about some intraclass correlation coefficients. Psychol Methods 1:30–46CrossRef
46.
go back to reference Lohr KN, Aaronson NK, Alonso J et al (1996) Evaluating quality of life and health status instruments: development of scientific review criteria. Clin Therapeutics 18:979–992CrossRef Lohr KN, Aaronson NK, Alonso J et al (1996) Evaluating quality of life and health status instruments: development of scientific review criteria. Clin Therapeutics 18:979–992CrossRef
47.
go back to reference McHorney CA, Ware JEJ, Raczek AE (1993) 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 31:247–263PubMedCrossRef McHorney CA, Ware JEJ, Raczek AE (1993) 36-Item Short-Form Health Survey (SF-36): II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care 31:247–263PubMedCrossRef
48.
go back to reference Spearman CE (1904) The proof and measurement of association between two things. American J Psychol 15:72–101CrossRef Spearman CE (1904) The proof and measurement of association between two things. American J Psychol 15:72–101CrossRef
49.
go back to reference Cano S, Warner T, Thompson A, Bhatia K, Fitzpatrick R, Hobart J (2008) The cervical dystonia impact profile (CDIP-58): can a Rasch developed patient reported outcome measure satisfy traditional psychometric criteria? Health Qual Life Outcomes 6:58PubMedCrossRef Cano S, Warner T, Thompson A, Bhatia K, Fitzpatrick R, Hobart J (2008) The cervical dystonia impact profile (CDIP-58): can a Rasch developed patient reported outcome measure satisfy traditional psychometric criteria? Health Qual Life Outcomes 6:58PubMedCrossRef
50.
go back to reference Cohen J, Cohen P, West S, Aiken L (2003) Applied multiple regression/correlation analysis for the behavioral sciences. Erlbaum, Hillsdale Cohen J, Cohen P, West S, Aiken L (2003) Applied multiple regression/correlation analysis for the behavioral sciences. Erlbaum, Hillsdale
51.
go back to reference Freeman JA, Hobart JC, Langdon DW, Thompson AJ (2000) Clinical appropriateness: a key factor in outcome measure selection. The 36-item Short Form Health Survey in multiple sclerosis. J Neurol Neurosurg Psychiatry 68:150–156PubMedCrossRef Freeman JA, Hobart JC, Langdon DW, Thompson AJ (2000) Clinical appropriateness: a key factor in outcome measure selection. The 36-item Short Form Health Survey in multiple sclerosis. J Neurol Neurosurg Psychiatry 68:150–156PubMedCrossRef
52.
go back to reference Riazi A, Hobart J, Lamping D, Fitzpatrick R, Thompson A (2002) Multiple Sclerosis Impact Scale (MSIS-29): reliability and validity in hospital based samples. J Neurol Neurosurg Psychiatry 73:701–704PubMedCrossRef Riazi A, Hobart J, Lamping D, Fitzpatrick R, Thompson A (2002) Multiple Sclerosis Impact Scale (MSIS-29): reliability and validity in hospital based samples. J Neurol Neurosurg Psychiatry 73:701–704PubMedCrossRef
53.
go back to reference Cano S, Hobart J, Edwards M et al (2006) CDIP-58 can measure the impact of botulinum toxin treatment in cervical dystonia. Neurology 67:2230–2232PubMedCrossRef Cano S, Hobart J, Edwards M et al (2006) CDIP-58 can measure the impact of botulinum toxin treatment in cervical dystonia. Neurology 67:2230–2232PubMedCrossRef
54.
go back to reference Bentler P, Chou C (1987) Practical issues in structural modelling. Sociol Methods Res 16:78–117CrossRef Bentler P, Chou C (1987) Practical issues in structural modelling. Sociol Methods Res 16:78–117CrossRef
55.
go back to reference Hancock G, Freeman M (2001) Power and sample size for the root mean square error of approximation test of not close fit in structural equation modelling. Educ Psychol Meas 61:741–758CrossRef Hancock G, Freeman M (2001) Power and sample size for the root mean square error of approximation test of not close fit in structural equation modelling. Educ Psychol Meas 61:741–758CrossRef
56.
go back to reference Muthén L, Muthén B (2002) How to use Monte Carlo study to decide on sample size and determine power. Struct Equ Model 9:599–620CrossRef Muthén L, Muthén B (2002) How to use Monte Carlo study to decide on sample size and determine power. Struct Equ Model 9:599–620CrossRef
Metadata
Title
What sample sizes for reliability and validity studies in neurology?
Authors
Jeremy C. Hobart
Stefan J. Cano
Thomas T. Warner
Alan J. Thompson
Publication date
01-12-2012
Publisher
Springer-Verlag
Published in
Journal of Neurology / Issue 12/2012
Print ISSN: 0340-5354
Electronic ISSN: 1432-1459
DOI
https://doi.org/10.1007/s00415-012-6570-y

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