The DOI matches its Crossref record; 49 of the 50 references it cites were found in a registry or an index.
Sample size in factor analysis.
Abstract
The factor analysis literature includes a range of recommendations regarding the minimum sample size necessary to obtain factor solutions that are adequately stable and that correspond closely to population factors. A fundamental misconception about this issue is that the minimum sample size, or the minimum ratio of sample size to the number of variables, is invariant across studies. In fact, necessary sample size is dependent on several aspects of any given study, including the level of communality of the variables and the level of overdetermination of the factors. The authors present a theoretical and mathematical framework that provides a basis for understanding and predicting these effects. The hypothesized effects are verified by a sampling study using artificial data. Results demonstrate the lack of validity of common rules of thumb and provide a basis for establishing guidelines for sample size in factor analysis. In the factor analysis literature, much attention has be;;n given to the issue of sample size. It is widely understood that the use of larger samples in applica-tions of factor analysis tends to provide results such that sample factor loadings are more precise estimates of population loadings and are also more stable, or les s variable, across repeated sampling. Despite gen-eral agreement on this matter, there is considerable di'/ergence of opinion and evidence about the ques-tion of how large a sample is necessary to adequately acnieve these objectives. Recommendations and find-ings about this issue are diverse and often contradic-tory. The objectives of this article are to provide a
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“recent simulations show that the sample size required to recover a stable factor structure is a joint function of number of factors, number of items per factor (with the required sample size stabilizing after 6–10 items per factor), and strength of factor loadings (MacCallum et al., 1999; Mundfrom et al., 2005).”
From The structure of adult ADHD. (2017) · cites this paper as MacCallum et al., 1999
In the citing paper
“Additionally, SEM flexibility allowing the examination of complex associations, multiple data types, model and/or group comparisons thus, developing general rules regarding sample size requirements are impractical (MacCallum et al., 1999; Wolf et al., 2013).”
From Applied Psychometrics: Sample Size and Sample Power Considerations in Factor Analysis (EFA, CFA) and SEM in General (2018) · cites this paper as MacCallum et al., 1999
In the citing paper
“While this sample size may not be considered very large, it is much in line with sample sizes in other strategy studies (Phelan, Ferreira, and Salvador, 2002) and exceeds common recommendations for advanced statistical analyses (e.g., MacCallum et al., 1999).”
From On the contingent value of dynamic capabilities for competitive advantage: The nonlinear moderating effect of environmental dynamism (2014) · cites this paper as MacCallum et al., 1999
In the citing paper
“According to this rule, data collection process was initiated with the aim of reaching at least 150 patients, which is five times of 30 questions.”
From Turkish Translation of the Patterns of Activity Measure-Pain in Patients with Chronic Low Back and Neck Pain: Validity and Reliability. (2022) · cites this paper as MacCallum et al., 1999
In the citing paper
“We therefore followed the recommendations of MacCallum et al. (1999) and Schönbrodt and Perugini (2013) and aimed to collect data from ~300 participants using each technology.”
From Technology evaluations are associated with psychological need satisfaction across different spheres of experience: an application of the METUX scales (2023) · cites this paper as MacCallum et al., 1999
In the citing paper
“Following the recommendations of MacCallum et al. (1999) regarding sample size for factor analyses, we aimed to collect data from 300 participants (150 participants who use Facebook and 150 participants who use virtual learning platforms).”
From Technology evaluations are associated with psychological need satisfaction across different spheres of experience: an application of the METUX scales (2023) · cites this paper as MacCallum et al., 1999
In the citing paper
“The minimum sample size was estimated to be 360 participants following the established guidelines for survey validation studies, considering 36 items with 10 participants per item [42-44].”
From Assessing Health Students' Attitudes and Usage of ChatGPT in Jordan: Validation Study (2023) · cites this paper as [43]
Citations
Cites
Alternative Ways of Assessing Model Fit
Browne, M. W., & Cudeck, R. (1992) · Sociological Methods & Research · doi:10.1177/0049124192021002005 · Cited by 27,200
Power analysis and determination of sample size for covariance structure modeling.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996) · Psychological Methods · doi:10.1037/1082-989x.1.2.130 · Cited by 10,418
Self-citationMultivariate Statistical Methods
(2008) · Springer eBooks · doi:10.1007/978-1-4020-5614-7_2263 · Cited by 5,584
Harman, H. H. (1960) · Cited by 5,148
A First Course in Factor Analysis
Comrey, A. L., & Lee, H. B. (2013) · doi:10.4324/9781315827506 · Cited by 4,546
A First Course in Factor Analysis
Price, B., Comrey, A. L., & Lee, H. B. (1993) · Technometrics · doi:10.1080/00401706.1993.10485363 · Cited by 3,512
Merrifield, P. R., & Harman, H. H. (1969) · American Educational Research Journal · doi:10.2307/1161864 · Cited by 2,574
Factor Analysis as a Statistical Method.
Browne, M. W., Lawley, D., & Maxwell, A. E. (1964) · Journal of the Royal Statistical Society Series D (The Statistician) · doi:10.2307/2986693 · Cited by 2,067
Anderson, J. C., & Gerbing, D. (1984) · Psychometrika · doi:10.1007/bf02294170 · Cited by 1,775
Handbook for the sixteen personality factor questionnaire (16 PF)
Cattell, R. B., Eber, H. W., & Tatsuoka, M. M. (1970) · Medical Entomology and Zoology · Cited by 1,618
Affects of variable and subject sampling on factor pattern recovery.
Velicer, W. F., & Fava, J. L. (1998) · Psychological Methods · doi:10.1037/1082-989x.3.2.231 · Cited by 998 · cited 11×
“These results are consistent with findings by Velicer and Fava (1998) and others.”
BackgroundResultInfluentialThe Foundations of Factor Analysis.
Sheth, J. N., & Mulaik, S. A. (1975) · Journal of the American Statistical Association · doi:10.2307/2285414 · Cited by 977
Multivariate Statistical Methods.
Chambers, J. M., & Morrison, D. F. (1967) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2982527 · Cited by 924
Multivariate Analysis: The Need for Data, and other Problems
Everitt, B. J. (1975) · The British Journal of Psychiatry · doi:10.1192/bjp.126.3.237 · Cited by 779
Factor Analysis as a Statistical Method.
Browne, M. W., Lawley, D. N., & Maxwell, A. E. (1973) · Journal of the American Statistical Association · doi:10.2307/2284191 · Cited by 733
Factor Analysis and Related Methods
Widaman, K. F., & McDonald, R. P. (1987) · Journal of Educational Statistics · doi:10.2307/1164692 · Cited by 668
Self-citationNonconvergence, Improper Solutions, and Starting Values in Lisrel Maximum Likelihood Estimation
Boomsma, A. (1985) · Psychometrika · doi:10.1007/bf02294248 · Cited by 621
The scientific use of factor analysis: Raymond B. Cattell Plenum Press, £20.48
Hanka, R. (1981) · Journal of Biomedical Engineering · doi:10.1016/0141-5425(81)90019-4 · Cited by 551
Arrindell, W. A., & van der Ende, J. (1985) · Applied Psychological Measurement · doi:10.1177/014662168500900205 · Cited by 550
Factor Analysis and Related Methods
McDonald, R. P. (2014) · Psychology Press eBooks · doi:10.4324/9781315802510 · Cited by 543
Kline, P. (1979) · Medical Entomology and Zoology · Cited by 503
Factor Analysis as A Statistical Method.
Hills, M., Lawley, D. N., & Maxwell, A. E. (1972) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344634 · Cited by 503
Jennrich, R. I., & Sampson, P. F. (1966) · Psychometrika · doi:10.1007/bf02289465 · Cited by 499
Designing Experiments and Analysing Data.
Morrey, G. H., Maxwell, S. E., & Delaney, H. D. (1991) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.2307/2347533 · Cited by 370
Evaluation of Factor Analytic Research Procedures by means of Simulated Correlation Matrices
Tucker, L. R., Koopman, R. F., & Linn, R. L. (1969) · Psychometrika · doi:10.1007/bf02290601 · Cited by 279
Cudeck, R. A., & O'Dell, L. L. (1994) · Psychological Bulletin · doi:10.1037/0033-2909.115.3.475 · Cited by 256
Model selection in covariance structures analysis and the "problem" of sample size: A clarification.
Cudeck, R. A., & Henly, S. J. (1991) · Psychological Bulletin · doi:10.1037/0033-2909.109.3.512 · Cited by 239
Representing sources of error in the common-factor model: Implications for theory and practice.
MacCallum, R. C., & Tucker, L. R. (1991) · Psychological Bulletin · doi:10.1037/0033-2909.109.3.502 · Cited by 235
Self-citationOn the Sampling Theory of Roots of Determinantal Equations
Girshick, M. A. (1939) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177732180 · Cited by 224
The observation to variable ratio in factor analysis.
Barrett, P. T., & Kline, P. (1981) · Cited by 211
A Comparison Of Component And Factor Patterns: A Monte Carlo Approach
Velicer, W. F., Peacock, A. C., & Jackson, D. N. (1982) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr1703_5 · Cited by 174
Gerbing, D. W., & Anderson, J. C. (1987) · Psychometrika · doi:10.1007/bf02293958 · Cited by 173
A Comparison of Factor Analytic Techniques
Browne, M. W. (1968) · Psychometrika · doi:10.1007/bf02289327 · Cited by 168
The study of sampling errors in factor analysis by means of artificial experiments.
Cliff, N., & Hamburger, C. D. (1967) · Psychological Bulletin · doi:10.1037/h0025178 · Cited by 152
The Effects of Overextraction on Factor and Component Analysis
Fava, J. L., & Velicer, W. F. (1992) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2703_5 · Cited by 152
The Distribution of Chance Congruence Coefficients from Simulated Data
Korth, B., & Tucker, L. R. (1975) · Psychometrika · doi:10.1007/bf02291763 · Cited by 117
The Effects of Underextraction in Factor and Component Analyses
Fava, J. L., & Velicer, W. F. (1996) · Educational and Psychological Measurement · doi:10.1177/0013164496056006001 · Cited by 86
An Evaluation of the Effects of Variable Sampling On Component, Image, and Factor Analysis
Velicer, W. F., & Fava, J. L. (1987) · Multivariate Behavioral Research · doi:10.1207/s15327906mbr2202_4 · Cited by 85
Standard Errors for Obliquely Rotated Factor Loadings
Jennrich, R. I. (1973) · Psychometrika · doi:10.1007/bf02291497 · Cited by 84
Designing Experiments and Analyzing Data
Patch, S. C., Maxwell, S. E., & Delaney, H. (1991) · Technometrics · doi:10.2307/1268809 · Cited by 79
Standard Errors for Rotated Factor Loadings
Archer, C. O., & Jennrich, R. I. (1973) · Psychometrika · doi:10.1007/bf02291496 · Cited by 74
SIMPLIFIED FORMULAE FOR STANDARD ERRORS IN MAXIMUM‐LIKELIHOOD FACTOR ANALYSIS
Jennrich, R. I. (1974) · British Journal of Mathematical and Statistical Psychology · doi:10.1111/j.2044-8317.1974.tb00533.x · Cited by 64
The Influence of Communality and N on the Sampling Distributions of Factor Loadings
Pennell, R. (1968) · Psychometrika · doi:10.1007/bf02290161 · Cited by 50
Cliff, N., & Pennell, R. (1967) · Psychometrika · doi:10.1007/bf02289594 · Cited by 39
Widaman, K. F., Kw, G., & Dc, G. (1987) · PubMed · Cited by 30
Self-citationApplications of a Certain Representation of the Wishart Matrix
Wijsman, R. A. (1959) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177706276 · Cited by 28
A Look, by Simulation, at the Validity of Some Asymptotic Distribution Results for Rotated Loadings
Archer, C. O., & Jennrich, R. I. (1976) · Psychometrika · doi:10.1007/bf02296974 · Cited by 12
STANDARD ERRORS FOR OBLIQUELY ROTATED FACTOR LOADINGS
Jennrich, R. I. (1973) · ETS Research Bulletin Series · doi:10.1002/j.2333-8504.1973.tb00640.x · Cited by 7
The distribution of chance congruence coefficients from simulated data
Korth, B., & Tucker, L. R. (n.d.) · RePEc: Research Papers in Economics · doi:10.1007/bf02294704 · Cited by 3
Cited by
Sorted by citations
Evaluating the use of exploratory factor analysis in psychological research.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.3.272 · Cited by 9,587
Self-citationTo parcel or not to parcel: Exploring the question, weighing the merits
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem0902_1 · Cited by 6,552
Self-citationBoateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quiñonez, H. R., & Young, S. L. (2018) · Frontiers in Public Health · doi:10.3389/fpubh.2018.00149 · Cited by 5,925
Scale Development Research: A Content Analysis and Recommendations for Best Practices
Worthington, R. L., & Whittaker, T. A. (2006) · The Counseling Psychologist · doi:10.1177/0011000006288127 · Cited by 4,087
Wolf, E. J., Harrington, K. M., Clark, S. L., & Miller, M. W. (2013) · Educational and Psychological Measurement · doi:10.1177/0013164413495237 · Cited by 3,931
Metadata
- Authors
- MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S.
- Affiliations
- The Ohio State University (US)
- University of California, Riverside (US)
- Venue
- Psychological Methods
- Published
- 1999-03
- Volume
- 4
- Issue
- 1
- Pages
- 84-99
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2122376319
- Cited by
- 5,497
- References
- 50
- Citations by year
- 2026: 456 · 2025: 418 · 2024: 359 · 2023: 311 · 2022: 359 · 2021: 396 · 2020: 413 · 2019: 318 · 2018: 286 · 2017: 276 · 2016: 259 · 2015: 226 · 2014: 230 · 2013: 233 · 2012: 177
- FWCI
- 27.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Methods (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- sample size, factor analysis, minimum sample size, communality, rules of thumb
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review