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Why sample selection matters in exploratory factor analysis: implications for the 12-item World Health Organization Disability Assessment Schedule 2.0

Gaskin, Cadeyrn J., Lambert, Sylvie D., Bowe, Steven J. and Orellana, Liliana 2017, Why sample selection matters in exploratory factor analysis: implications for the 12-item World Health Organization Disability Assessment Schedule 2.0, BMC medical research methodology, vol. 17, pp. 1-9, doi: 10.1186/s12874-017-0309-5.

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Title Why sample selection matters in exploratory factor analysis: implications for the 12-item World Health Organization Disability Assessment Schedule 2.0
Author(s) Gaskin, Cadeyrn J.
Lambert, Sylvie D.
Bowe, Steven J.ORCID iD for Bowe, Steven J. orcid.org/0000-0003-3813-842X
Orellana, LilianaORCID iD for Orellana, Liliana orcid.org/0000-0003-3736-4337
Journal name BMC medical research methodology
Volume number 17
Article ID 40
Start page 1
End page 9
Total pages 9
Publisher BioMed Central
Place of publication London, Eng.
Publication date 2017-03-11
ISSN 1471-2288
Keyword(s) exploratory factor analysis
eligibility criteria
sample selection
instrument validation
psychometric assessment
WHODAS 2.0
ICF
disability
Science & Technology
Life Sciences & Biomedicine
Health Care Sciences & Services
LIKERT VARIABLES
INDICATORS
METHODOLOGIES
PEOPLE
NUMBER
JIFFY
ITEM
Summary Background
Sample selection can substantially affect the solutions generated using exploratory factor analysis. Validation studies of the 12-item World Health Organization (WHO) Disability Assessment Schedule 2.0 (WHODAS 2.0) have generally involved samples in which substantial proportions of people had no, or minimal, disability. With the WHODAS 2.0 oriented towards measuring disability across six life domains (cognition, mobility, self-care, getting along, life activities, and participation in society), performing factor analysis with samples of people with disability may be more appropriate. We determined the influence of the sampling strategy on (a) the number of factors extracted and (b) the factor structure of the WHODAS 2.0.

Methods

Using data from adults aged 50+ from the six countries in Wave 1 of the WHO’s longitudinal Study on global AGEing and adult health (SAGE), we repeatedly selected samples (n = 750) using two strategies: (1) simple random sampling that reproduced nationally representative distributions of WHODAS 2.0 summary scores for each country (i.e., positively skewed distributions with many zero scores indicating the absence of disability), and (2) stratified random sampling with weights designed to obtain approximately symmetric distributions of summary scores for each country (i.e. predominantly including people with varying degrees of disability).

Results

Samples with skewed distributions typically produced one-factor solutions, except for the two countries with the lowest percentages of zero scores, in which the majority of samples produced two factors. Samples with approximately symmetric distributions, generally produced two- or three-factor solutions. In the two-factor solutions, the getting along domain items loaded on one factor (commonly with a cognition domain item), with remaining items loading on a second factor. In the three-factor solutions, the getting along and self-care domain items loaded separately on two factors and three other domains (mobility, life activities, and participation in society) on the third factor; the cognition domain items did not load together on any factor.

Conclusions
High percentages of participants with no disability (i.e., zero scores) produce heavily censored data (i.e., floor effects), limiting data heterogeneity and reducing the numbers of factors retained. The WHODAS 2.0 appears to have multiple closely-related factors. Samples of convenience and those collected for other purposes (e.g., general population surveys) would usually be inadequate for validating measures using exploratory factor analysis.
Language eng
DOI 10.1186/s12874-017-0309-5
Field of Research 111799 Public Health and Health Services not elsewhere classified
1117 Public Health And Health Services
Socio Economic Objective 970111 Expanding Knowledge in the Medical and Health Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2017, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30091953

Document type: Journal Article
Collections: Faculty of Health
PVC's Office - Health
Open Access Collection
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.