About

Paul Sackett is a Professor of Psychology at the University of Minnesota, affiliated with the College of Liberal Arts. His work focuses on the tension between designing selection systems to maximize job performance and to promote ethnic, racial, and gender diversity, with significant contributions to the legal, psychometric, and philosophical perspectives on affirmative action. Sackett has extensively studied the measurement and prediction of counterproductive behavior in the workplace, including integrity testing for screening prospective employees. He emphasizes the importance of methodological rigor and psychometric sophistication in personnel decision-making and has contributed to the assessment of managerial potential, particularly through the evaluation of assessment center techniques. His research also explores the role of personality in personnel selection, especially in the context of instructed versus natural faking studies. Sackett has held leadership roles such as President of the Society for Industrial and Organizational Psychology, editor of Personnel Psychology, and has received numerous awards for his contributions to the field.

Research topics

• Psychology
• Social psychology
• Applied psychology
• Computer science
• Statistics

Selected publications

• What do assessment center ratings reflect? Consistency and heterogeneity in variance composition across multiple samples

  Universität Zürich, ZORA · 2026-01-15

  articleOpen accessSenior author
  PublisherDOI

• Planned missingness to reduce survey length: A sheep in wolf’s clothing.

  Psychological Methods · 2026-02-05

  article

  Psychologists often have the need to reduce the length of a survey study to ensure data quality, meet practical constraints, or conserve participant resources. The present study explores a survey technique called planned missingness (PM) as an approach to reducing study length. We conducted a Monte Carlo simulation that directly compared using a PM design to the standard practice of using short forms of measures on their ability to reproduce true population intercorrelations. We manipulated a number of population and study characteristics, including the number of constructs, missingness level, sample size, true intercorrelations, as well as the manner in which short forms are developed, and their impact on the short form-planned missingness comparison. Results show that the two approaches perform comparably across a large number of conditions. Under simulated, idealized data conditions and using correctly specified models, short forms produce slightly more accurate estimates when empirically developed short forms are readily available for use. PM produces slightly more accurate estimates when short forms are developed not entirely empirically. However, discrepancies are small in general. Additional advantages and limitations of PM are discussed. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

  PublisherDOI

• Graduate grade inflation at a U.S. research-intensive university: A 22-year longitudinal analysis

  PLoS ONE · 2026-03-25 · 1 citations

  articleOpen accessSenior author

  The phenomenon of grade inflation has been studied extensively at high school and undergraduate levels, yet little is known about its occurrence in graduate education. This study bridges this gap by examining graduate grade inflation using data from one U.S. research intensive university, covering two decades of admissions across 75 master's programs (N = 24,815) and 78 doctoral programs (N = 15,701). Relying on both linear and ordinal multilevel models, we investigated the presence of grade inflation and potential variations by degree level and individual academic programs at the program level. Our findings provide preliminary evidence for the presence of graduate grade inflation and suggest that the magnitudes differ across individual academic programs. There is also evidence showing that the trend of grade inflation significantly differed across master's and doctoral programs. This apparent inflation undermines the signaling value of grades for employers and admission decisions in the labor market and academic selection, as well as for research, feedback, and learning purposes. Future research should replicate our findings using multi-institutional samples and examine drivers of graduate grade inflation to more accurately estimate its magnitude.

  PublisherDOI

• Graduate Grade Inflation at a U.S. Research-Intensive University: A 22-Year Longitudinal Analysis

  DOAJ (DOAJ: Directory of Open Access Journals) · 2026-01-01

  articleOpen accessSenior author
  Publisher

• Do Predictive Inferences Made from Admissions Test Scores Vary by Amount and Type of Test Preparation?

  Applied Measurement in Education · 2025-04-03

  article
  PublisherDOI

• What do assessment center ratings reflect? Consistency and heterogeneity in variance composition across multiple samples.

  Journal of Applied Psychology · 2025-09-29 · 2 citations

  articleSenior author

  = 4,963 assessees with 272,528 observations). This provides the first meta-analytic estimates of these effects, as well as insight into the extent to which findings from previous studies generalize to assessment center samples that differ in measurement design, industry, and purpose, and how heterogeneous these effects are across samples. Results were consistent with previous trends in the ranking of variance explained by key AC components (with assessee main effects and assessee-exercise effects being the largest variance components) and additionally emphasized the relevance of assessee-exercise-dimension effects. In addition, meta-analytic results suggested substantial heterogeneity in all reliable variance components (i.e., assessee main effect, assessee-exercise effect, assessee-dimension effect, and assessee-exercise-dimension effect) and in interrater reliability across assessment center samples. Aggregating AC ratings into higher level scores (i.e., overall AC scores, exercise-level scores, and dimension-level scores) reduced heterogeneity only slightly. Implications of the findings for a multifaceted assessment center functioning are discussed. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

  PublisherDOI

• Examining Gender-Based Differences in Quantitative Ratings and Narrative Comments in Faculty Assessments by Residents and Fellows

  Journal of Graduate Medical Education · 2025-06-01 · 1 citations

  articleOpen access

  ABSTRACT Background Learner assessments of faculty are widespread in medicine, yet concerns are growing about possible biases in these assessments and their associations with gender disparities. Objective To investigate gender-based differences in how residents and fellows describe faculty (rater effect) and how faculty are described (ratee effect) in faculty assessments, and their associations with teaching effectiveness ratings. Methods We analyzed 2164 trainee assessments of University of Minnesota Medical School faculty from 2019 to 2023 with trainee and faculty gender information and narrative comments. Using natural language processing, we categorized words and 2-word groups (n-grams) into communal (eg, caring, kind), standout (eg, outstanding, amazing), and agentic/ability (eg, assertive, controlling) groups. We examined gender-based differences in n-grams used by trainees (rater effect) and received by faculty (ratee effect), and relationships between n-gram and teaching effectiveness ratings. Results Women trainees used more communal (rater effect, incidence rate ratio [IRR]=1.36; 95% CI, 1.27-1.47), standout (IRR=1.20; 95% CI, 1.08-1.34), and agentic/ability words (IRR=1.37; 95% CI, 1.26-1.49; P <.001) than men trainees. Women faculty received fewer agentic/ability words than men faculty (ratee effect, IRR=0.83; 95% CI, 0.77-0.90; P <.001). Women trainees used fewer communal words when describing women faculty (interaction effect, IRR=0.84; 95% CI, 0.73-0.98; P <.05). Teaching effectiveness ratings correlated with faculty n-gram word frequency in standout (men: r s =0.29, women: r s = 0.28, P <.001) and communal categories (men: r s =0.23, P =.003; women: r s = 0.22, P =.01). Conclusions Women trainees used more communal, standout, and agentic/ability descriptors, while women faculty had fewer agentic/ability descriptors. Women trainees used fewer communal words when describing women faculty. Standout and communal word frequency predicted teaching effectiveness ratings for both genders.

  PublisherOA PDFDOI

• The relationship between personality and within-person within-semester performance variability

  Personality and Individual Differences · 2025-02-22

  article
  PublisherDOI

• Hiring People in Organizations: The State and Future of the Science

  Annual Review of Organizational Psychology and Organizational Behavior · 2025-08-27 · 3 citations

  articleOpen access1st authorCorresponding

  Here we review recent work in the personnel selection field. We open with two sections, the first focusing on meta-analytic validity research on well-established predictors and the second on new measurement approaches. These include moving from a holistic to a modular view of predictors; from face-to-face to asynchronous video interviews; from resumes to social media assessments; from multiple choice to constructed response; and to using artificial intelligence to develop, administer, and score tests, among approaches. We then review developments in estimating validity, including issues in correcting validity estimates for error of measurement and restriction of range. We address technical issues on the topics of fairness and bias, including Pareto optimization, effect size measures for predictive bias, and approaches to algorithmic bias mitigation, and offer insight into addressing the validity-diversity dilemma. We then discuss insights into applicant reactions to selection systems and perspectives of other stakeholders in the selection process.

  PublisherDOI

• Does It Matter Which Subtests We Use to Measure General Cognitive Ability? Group Differences Across Test Composites

  International Journal of Selection and Assessment · 2025-10-22

  articleOpen accessSenior author

  ABSTRACT We demonstrate that overreliance on the common convention in our field that virtually any composite of three or more specific cognitive tests will result in a robust measure of general cognitive ability (GCA) can lead to inconsistent inferences about the nature of subgroup differences in GCA. Using data from Project Talent and NLSY97, we examined how different composites of cognitively loaded tests can vary in terms of subgroup differences. After forming all possible three‐test composites in each dataset, we found that while these composites generally had very similar correlations with GCA, they varied much more widely in their degrees of gender and race/ethnic mean score differences. We discuss considerations that can aid in assembling test composites that better capture true subgroup differences.

  PublisherOA PDFDOI

Frequent coauthors

• Nathan R. Kuncel

  University of Minnesota

  93 shared

• Filip Lievens

  Singapore Management University

  91 shared

• Michael J. Cullen

  Columbia University

  47 shared

• Jeffrey A. Dahlke

  37 shared

• Winny Shen

  York University

  36 shared

• Adam Beatty

  American Public University System

  34 shared

• Christopher M. Berry

  26 shared

• Chad H. Van Iddekinge

  26 shared

Awards & honors

• Distinguished Service Contribution Award, Society for Indust…
• Distinguished Scientific Contribution Award, Society for Ind…
• Distinguished Teaching Contribution Award, Society for Indus…
• Honorary Doctorate, Ghent University, Belgium (2011)
• Herbert G. Heneman Jr. Career Achievement Award, Human Resou…