SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test

O’connor, Brian P.

doi:10.3758/bf03200807

Cited by 4,116Psychometric Methodologies and TestingStatistical Methods and ApplicationsMental Health Research Topics

SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test

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O’connor, Brian P.·2000·Behavior Research Methods, Instruments, & Computers

DOI 10.3758/bf03200807

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Abstract

Popular statistical software packages do not have the proper procedures for determining the number of components in factor and principal components analyses. Parallel analysis and Velicer's minimum average partial (MAP) test are validated procedures, recommended widely by statisticians. However, many researchers continue to use alternative, simpler, but flawed procedures, such as the eigenvalues-greater-than-one rule. Use of the proper procedures might be increased if these procedures could be conducted within familiar software environments. This paper describes brief and efficient programs for using SPSS and SAS to conduct parallel analyses and the MAP test.

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MAP suggests the smallest number of factors, while PA-SMC95 suggests the largest number of factors.
“MAP suggests the smallest number of factors, while PA-SMC95 suggests the largest number of factors (O ' connor, 2000).”
From Reliability and validity of the Japanese version of the experiential avoidance in caregiving questionnaire (EACQ) (2023) · cites this paper as O'Connor, 2000
The Parallel Analysis section (page not available) says MAP tends toward underextraction and parallel analysis toward overextraction when they err, which supports the direction of the comparison. It also says the methods typically recommend the same number of components. The paper does not establish that MAP gives the smallest estimate or that the specific PA-SMC95 variant gives the largest. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Parallel analysis indicated retaining five factors that were theoretically consistent.
“Empirically, parallel analysis (O’connor, 2000) indicated retention of five, theoretically consistent factors”
From The metacognitive processes of decentering scale: Development and initial validation of trait and state versions (2020) · cites this paper as O’connor, 2000

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“The estimated number of components in the scale was initially determined using both parallel analyses (95 th percentile) and the Velicer's Minimum Average Partial Method (MAP, [27]) using a script developed by O'Connor [ 28 ].”
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A Comparison of Five Rules for Determining the Number of Components in Complex Patterns
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Authors: O’connor, B. P.
Affiliations: Lakehead University (CA)
Corresponding author: O’connor, Brian P.
ORCID: O’connor, Brian P.
Venue: Behavior Research Methods, Instruments, & Computers
Publisher: Springer Science and Business Media LLC
Published: 2000-09
Volume: 32
Issue: 3
Pages: 396-402
ISSN: 0743-3808 (ISSN-L)
1532-5970
DOI: 10.3758/bf03200807
OpenAlex: W2124563089
Cited by: 4,116
References: 24
Citations by year: 2026: 140 · 2025: 161 · 2024: 212 · 2023: 190 · 2022: 234 · 2021: 268 · 2020: 285 · 2019: 245 · 2018: 249 · 2017: 286 · 2016: 227 · 2015: 252 · 2014: 221 · 2013: 207 · 2012: 169
FWCI: 12.64
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.springer.com/tdm (tdm)
Locations: Behavior Research Methods, Instruments, & Computers (publishedVersion)
PubMed (publishedVersion)
Funders: Social Sciences and Humanities Research Council of Canada
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Keywords: number of components, parallel analysis, factor analysis, principal component analysis, SAS program
MeSH terms: Factor Analysis, Statistical, Psychology, Software

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SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test

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