The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations
Open accessOverview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
On the practice of dichotomization of quantitative variables.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.19 · Cited by 3,538
Interaction Effects in Multiple Regression
Jaccard, J., & Turrisi, R. (2003) · doi:10.4135/9781412984522 · Cited by 1,797
Research works printed but not linked: 19
- Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage.
- Bauer, D. J., & Curran, P. J. (2005). Probing interactions in fixed and multilevel regression: Inferential and graphical techniques. Multivariate Behavioral Research, 40, 373–400. · DOI · Paper page
- Bissonnette, V., Ickes, W., Bernstein, I., & Knowles, E. (1990). Personality moderating variables: A warning about statistical artifact and a comparison of analytic techniques. Journal of Personality, 58, 567–587. · DOI
- Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.
- Cronbach, L. J. (1987). Statistical tests for moderator variables: Flaws in analyses recently proposed. Psychological Bulletin, 102, 414–417. · doi:10.1037/0033-2909.102.3.414 · Paper page
- Darlington, R. B. (1990). Regression and linear models. New York: McGraw-Hill.
- Hayes, A. F. (2005). Statistical methods for communication science. Mahwah, NJ: Erlbaum.
- Irwin, J. R., & McClelland, G. H. (2001). Misleading heuristics and moderated multiple regression models. Journal of Marketing Research, 38, 100–109. · DOI · Paper page
- Johnson, P. O., & Fay, L. C. (1950). The Johnson-Neyman technique, its theory and application. Psychometrika, 15, 349–367. · DOI · Paper page
- Johnson, P. O., & Neyman, J. (1936). Tests of certain linear hypotheses and their application to some educational problems. Statistical Research Memoirs, 1, 57–93.
- Karpman, M. B. (1983). The Johnson-Neyman technique using SPSS or BMDP. Educational & Psychological Measurement, 43, 137–147. · DOI
- Karpman, M. B. (1986). Comparing two non-parallel regression lines with the parametric alternative to analysis of covariance using SPSS-X or SAS—the Johnson-Neyman technique. Educational & Psychologicals Measurement, 46, 639–644. · doi:10.1177/0013164486463018
- Kromrey, J. D., & Foster-Johnson, L. (1998). Mean centering in moderated multiple regression: Much ado about nothing. Educational & Psychological Measurement, 58, 42–67. · DOI
- Newsom, J. T., Prigerson, H. G., Schulz, R., & Reynolds, C. F., III (2003). Investigating moderator hypotheses in aging research: Statistical, methodological, and conceptual difficulties with comparing separate regressions. International Journal of Aging & Human Development, 57, 119–150. · DOI
- O’Connor, B. P. (1998). SIMPLE: All-in-one programs for exploring interactions in moderated multiple regression. Educational & Psychological Measurement, 58, 836–840. · DOI
- Potthoff, R. F. (1964). On the Johnson-Neyman technique and some extensions thereof. Psychometrika, 29, 241–256. · DOI
- Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational & Behavioral Statistics, 31, 437–448. · DOI · Paper page
- Rogosa, D. (1980). Comparing nonparallel regression lines. Psychological Bulletin, 88, 307–321. · doi:10.1037/0033-2909.88.2.307 · Paper page
- Stone-Romero, E. F., & Anderson, L. E. (1994). Relative power of moderated multiple regression and the comparison of subgroup correlation coefficients for detecting moderator effects. Journal of Applied Psychology, 79, 354–359. · doi:10.1037/0021-9010.79.3.354 · Paper page
Cited by
Hayes, A. F. (2018) · Communication Monographs · doi:10.1080/03637751.2017.1352100 · Cited by 3,516
Self-citationHayes, A. F., & Rockwood, N. J. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.11.001 · Cited by 2,350
Self-citationEllis, W. E., Dumas, T. M., & Forbes, L. M. (2020) · Canadian Journal of Behavioural Science / Revue canadienne des sciences du comportement · doi:10.1037/cbs0000215 · Cited by 830
Shankar (2013) · doi:10.1097/psy.0b013e31827f09cd · Cited by 635
Emotional eating, depressive symptoms and self-reported food consumption. A population-based study.
Konttinen, H., Männistö, S., Sarlio-Lähteenkorva, S., Silventoinen, K., & Haukkala, A. (2010) · Appetite · doi:10.1016/j.appet.2010.01.014 · Cited by 546
Metadata
- Authors
- Hayes, A. F., & Matthes, J.
- Venue
- Behavior Research Methods
- Published
- 2009-08
- Volume
- 41
- Issue
- 3
- Pages
- 924-936
- ISSN
- 1554-351X (ISSN-L)
- 1554-3528
- OpenAlex
- W2093222646
- Cited by
- 2,448
- References
- 2
- FWCI
- 80.90
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. https://app.cochat.ai/papers/10.3758/brm.41.3.924
- The paper
- Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing interactions in OLS and logistic regression: SPSS and SAS implementations. Behavior Research Methods. https://doi.org/10.3758/brm.41.3.924
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
