Daniel McNeish

11.4k total citations · 10 hit papers
107 papers, 7.2k citations indexed

About

Daniel McNeish is a scholar working on Statistics and Probability, Management Science and Operations Research and Experimental and Cognitive Psychology. According to data from OpenAlex, Daniel McNeish has authored 107 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Statistics and Probability, 33 papers in Management Science and Operations Research and 21 papers in Experimental and Cognitive Psychology. Recurrent topics in Daniel McNeish's work include Psychometric Methodologies and Testing (30 papers), Statistical Methods and Bayesian Inference (29 papers) and Mental Health Research Topics (15 papers). Daniel McNeish is often cited by papers focused on Psychometric Methodologies and Testing (30 papers), Statistical Methods and Bayesian Inference (29 papers) and Mental Health Research Topics (15 papers). Daniel McNeish collaborates with scholars based in United States, Netherlands and Norway. Daniel McNeish's co-authors include Laura M. Stapleton, Melissa Gordon Wolf, Ellen L. Hamaker, Gregory R. Hancock, Melissa Gordon Wolf, Ken Kelley, Ji An, Kathryn R. Wentzel, Denis Dumas and Jeffrey R. Harring and has published in prestigious journals such as Journal of Applied Psychology, American Psychologist and Annual Review of Psychology.

In The Last Decade

Daniel McNeish

101 papers receiving 7.0k citations

Hit Papers

Thanks coefficient alpha, we’ll take it from here. 2014 2026 2018 2022 2017 2016 2014 2016 2020 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Thanks coefficient alpha, we’ll take it from here.
    2017 1.5k citations Daniel McNeish Psychological Methods profile →
  2. On the unnecessary ubiquity of hierarchical linear modeling.
    2016 566 citations Daniel McNeish, Laura M. Stapleton et al. Psychological Methods profile →
  3. The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration
    2014 492 citations Daniel McNeish, Laura M. Stapleton profile →
  4. On Using Bayesian Methods to Address Small Sample Problems
    2016 357 citations Daniel McNeish Structural Equation Modeling A Multidisciplinary Journal profile →
  5. Thinking twice about sum scores
    2020 352 citations Daniel McNeish et al. Behavior Research Methods profile →
  6. A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus.
    2019 314 citations Daniel McNeish et al. Psychological Methods profile →
  7. Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences
    2015 290 citations Daniel McNeish Multivariate Behavioral Research profile →
  8. Modeling Clustered Data with Very Few Clusters
    2016 273 citations Daniel McNeish, Laura M. Stapleton Multivariate Behavioral Research profile →
  9. The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models
    2017 250 citations Daniel McNeish et al. profile →
  10. Dynamic fit index cutoffs for confirmatory factor analysis models.
    2021 214 citations Daniel McNeish et al. Psychological Methods profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel McNeish United States 31 1.6k 1.5k 1.4k 1.2k 1.0k 107 7.2k
Ken Kelley United States 35 1.8k 1.1× 1.5k 1.0× 1.2k 0.8× 766 0.6× 1.2k 1.2× 77 8.4k
Gregory R. Hancock United States 42 1.5k 1.0× 1.6k 1.1× 1.0k 0.7× 1.1k 0.9× 1.5k 1.4× 162 7.7k
Mirjam Moerbeek Netherlands 27 1.1k 0.7× 1.3k 0.9× 922 0.6× 1.1k 0.9× 1.8k 1.7× 106 8.1k
Mijke Rhemtulla United States 32 1.9k 1.2× 1.7k 1.1× 2.6k 1.8× 716 0.6× 1.1k 1.1× 83 7.3k
Mike W.‐L. Cheung Singapore 46 1.9k 1.2× 1.7k 1.1× 1.4k 0.9× 788 0.6× 1.6k 1.5× 104 9.5k
Alexander Robitzsch Germany 32 759 0.5× 1.4k 0.9× 1.3k 0.9× 1.7k 1.4× 732 0.7× 171 5.5k
Urbano Lorenzo‐Seva Spain 40 2.6k 1.7× 2.3k 1.5× 1.4k 0.9× 1.1k 0.9× 1.1k 1.0× 139 8.3k
Jelte M. Wicherts Netherlands 48 1.5k 1.0× 1.6k 1.0× 2.6k 1.8× 449 0.4× 1.3k 1.2× 126 8.9k
Tenko Raykov United States 43 1.9k 1.2× 2.1k 1.4× 1.4k 1.0× 1.2k 1.0× 1.5k 1.5× 235 10.1k
Deborah L Bandalos United States 26 2.2k 1.4× 2.0k 1.3× 1.4k 1.0× 1.6k 1.3× 1.4k 1.4× 60 7.3k

Countries citing papers authored by Daniel McNeish

Since Specialization
Citations

This map shows the geographic impact of Daniel McNeish's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel McNeish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel McNeish more than expected).

Fields of papers citing papers by Daniel McNeish

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel McNeish. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel McNeish. The network helps show where Daniel McNeish may publish in the future.

Co-authorship network of co-authors of Daniel McNeish

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel McNeish. A scholar is included among the top collaborators of Daniel McNeish based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel McNeish. Daniel McNeish is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
McNeish, Daniel, Sophia M. Bartels, Kathleen Bell, et al.. (2025). Adherence to a digital therapeutic mediates the relationship between momentary self-regulation and health risk behaviors. Frontiers in Digital Health. 7. 1467772–1467772. 1 indexed citations
3.
McNeish, Daniel, et al.. (2025). SRMR for Models with Covariates. Psychometrika. 90(1). 24–46. 3 indexed citations
4.
McNeish, Daniel. (2025). Less Heuristic Approximate Local Fit Evaluation in Structural Equation Models. Structural Equation Modeling A Multidisciplinary Journal. 32(4). 590–605. 1 indexed citations
5.
McNeish, Daniel. (2024). Practical Implications of Sum Scores Being Psychometrics’ Greatest Accomplishment. Psychometrika. 89(4). 1148–1169. 8 indexed citations
6.
Guttmannova, Katarína, et al.. (2023). Tobacco Use Patterns From Adolescence to Young Adulthood Among Latinx Youth From Rural Communities. Journal of Adolescent Health. 73(4). 761–768. 3 indexed citations
7.
McNeish, Daniel, et al.. (2023). Dynamic structural equation models with binary and ordinal outcomes in Mplus. Behavior Research Methods. 56(3). 1506–1532. 14 indexed citations
8.
Aitken, A. Angelique, Steve Graham, & Daniel McNeish. (2022). The effects of choice versus preference on writing and the mediating role of perceived competence.. Journal of Educational Psychology. 114(8). 1844–1865. 6 indexed citations
9.
McNeish, Daniel. (2020). Specifying Location-Scale Models for Heterogeneous Variances as Multilevel SEMs. Organizational Research Methods. 24(3). 630–653. 28 indexed citations
10.
Dumas, Denis, Daniel McNeish, & Jeffrey A. Greene. (2020). Dynamic measurement: A theoretical–psychometric paradigm for modern educational psychology. Educational Psychologist. 55(2). 88–105. 24 indexed citations
11.
McNeish, Daniel, et al.. (2020). Response heterogeneity to lifestyle intervention among Latino adolescents. Pediatric Diabetes. 21(8). 1430–1436. 4 indexed citations
12.
Somers, Jennifer A., Margaret Kerr, Daniel McNeish, et al.. (2019). Quantitatively representing real-time emotion dynamics: Attachment-based differences in mothers’ emotion experiences.. Journal of Family Psychology. 34(4). 480–489. 9 indexed citations
13.
Smid, Sanne C., Daniel McNeish, Milica Miočević, & Rens van de Schoot. (2019). Bayesian Versus Frequentist Estimation for Structural Equation Models in Small Sample Contexts: A Systematic Review. Structural Equation Modeling A Multidisciplinary Journal. 27(1). 131–161. 151 indexed citations
14.
McNeish, Daniel, Denis Dumas, & Kevin J. Grimm. (2019). Estimating New Quantities from Longitudinal Test Scores to Improve Forecasts of Future Performance. Multivariate Behavioral Research. 55(6). 894–909. 9 indexed citations
15.
Elzakkers, Isis F.F.M., Unna N. Danner, Lot Sternheim, et al.. (2017). Mental capacity to consent to treatment and the association with outcome: A longitudinal study in patients with anorexia nervosa. BJPsych Open. 3(3). 147–153. 11 indexed citations
16.
McNeish, Daniel, et al.. (2016). On the unnecessary ubiquity of hierarchical linear modeling.. Psychological Methods. 22(1). 114–140. 566 indexed citations breakdown →
17.
McNeish, Daniel & Kathryn R. Wentzel. (2016). Accommodating Small Sample Sizes in Three-Level Models When the Third Level is Incidental. Multivariate Behavioral Research. 52(2). 200–215. 50 indexed citations
18.
McNeish, Daniel & Laura M. Stapleton. (2016). Modeling Clustered Data with Very Few Clusters. Multivariate Behavioral Research. 51(4). 495–518. 273 indexed citations breakdown →
19.
McNeish, Daniel. (2015). Using Lasso for Predictor Selection and to Assuage Overfitting: A Method Long Overlooked in Behavioral Sciences. Multivariate Behavioral Research. 50(5). 471–484. 290 indexed citations breakdown →
20.
McNeish, Daniel, et al.. (2015). A Multidimensional Perspective of College Readiness: Relating Student and School Characteristics to Performance on the ACT®. ACT Research Report Series 2015 (6).. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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