The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Doctoral training in statistics, measurement, and methodology in psychology: Replication and extension of Aiken, West, Sechrest, and Reno's (1990) survey of PhD programs in North America.
Abstract
In a survey of all PhD programs in psychology in the United States and Canada, the authors documented the quantitative methodology curriculum (statistics, measurement, and research design) to examine the extent to which innovations in quantitative methodology have diffused into the training of PhDs in psychology. In all, 201 psychology PhD programs (86%) participated. This survey replicated and extended a previous survey (L. S. Aiken, S. G. West, L. B. Sechrest, & R. R. Reno, 1990), permitting examination of curriculum development. Most training supported laboratory and not field research. The median of 1.6 years of training in statistics and measurement was mainly devoted to the modally 1-year introductory statistics course, leaving little room for advanced study. Curricular enhancements were noted in statistics and to a minor degree in measurement. Additional coverage of both fundamental and innovative quantitative methodology is needed. The research design curriculum has largely stagnated, a cause for great concern. Elite programs showed no overall advantage in quantitative training. Forces that support curricular innovation are characterized. Human capital challenges to quantitative training, including recruiting and supporting young quantitative faculty, are discussed. Steps must be taken to bring innovations in quantitative methodology into the curriculum of PhD programs in psychology.
Overview
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
Missing data: our view of the state of the art
Schafer, J. L., & Graham, J. W. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.2.147 · Cited by 11,638
Introduction to Statistical Mediation Analysis
MacKinnon, D. P. (2012) · doi:10.4324/9780203809556 · Cited by 5,618
Causal Inference Using Potential Outcomes: Design, Modeling, Decisions
Rubin, D. B. (2005) · Journal of the American Statistical Association · doi:10.1198/016214504000001880 · Cited by 2,173
Using SAS PROC MIXED to Fit Multilevel Models, Hierarchical Models, and Individual Growth Models
Singer, J. D. (1998) · Journal of Educational and Behavioral Statistics · doi:10.2307/1165280 · Cited by 1,092
Cited by
On making causal claims: A review and recommendations
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010) · The Leadership Quarterly · doi:10.1016/j.leaqua.2010.10.010 · Cited by 2,441
Exploratory Factor Analysis: A Guide to Best Practice
Watkins, M. W. (2018) · Journal of Black Psychology · doi:10.1177/0095798418771807 · Cited by 2,218
Construct Validation in Social and Personality Research: Current Practice and Recommendations
Flake, J. K., Pek, J., & Hehman, E. (2017) · Social Psychological and Personality Science · doi:10.1177/1948550617693063 · Cited by 697
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2014) · Oxford Handbooks Online · doi:10.1093/oxfordhb/9780199755615.013.007 · Cited by 305
An Ounce of Prevention Is Worth a Pound of Cure: Improving Research Quality Before Data Collection
Aguinis, H., & Vandenberg, R. J. (2014) · Annual Review of Organizational Psychology and Organizational Behavior · doi:10.1146/annurev-orgpsych-031413-091231 · Cited by 304
Metadata
- Authors
- Aiken, L. S., West, S. G., & Millsap, R. E.
- Venue
- American Psychologist
- Published
- 2008
- Volume
- 63
- Issue
- 1
- Pages
- 32-50
- ISSN
- 0003-066X (ISSN-L)
- 1935-990X
- OpenAlex
- W1994757268
- Cited by
- 187
- References
- 4
- FWCI
- 9.56
- Type
- journal article
- Language
- en
- Open access
- closed
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: Doctoral training in statistics, measurement, and methodology in psychology: Replication and extension of Aiken, West, Sechrest, and Reno's (1990) survey of PhD programs in North America. https://app.cochat.ai/papers/10.1037/0003-066x.63.1.32
- The paper
- Aiken, L. S., West, S. G., & Millsap, R. E. (2008). Doctoral training in statistics, measurement, and methodology in psychology: Replication and extension of Aiken, West, Sechrest, and Reno's (1990) survey of PhD programs in North America. American Psychologist. https://doi.org/10.1037/0003-066x.63.1.32
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.