David Rindskopf

8.3k total citations · 2 hit papers
91 papers, 5.7k citations indexed

About

David Rindskopf is a scholar working on Statistics and Probability, Management Science and Operations Research and Developmental and Educational Psychology. According to data from OpenAlex, David Rindskopf has authored 91 papers receiving a total of 5.7k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Statistics and Probability, 17 papers in Management Science and Operations Research and 14 papers in Developmental and Educational Psychology. Recurrent topics in David Rindskopf's work include Statistical Methods and Bayesian Inference (12 papers), Optimal Experimental Design Methods (12 papers) and Behavioral and Psychological Studies (10 papers). David Rindskopf is often cited by papers focused on Statistical Methods and Bayesian Inference (12 papers), Optimal Experimental Design Methods (12 papers) and Behavioral and Psychological Studies (10 papers). David Rindskopf collaborates with scholars based in United States, United Kingdom and Germany. David Rindskopf's co-authors include William R. Shadish, Samuel L. Odom, Thomas R. Kratochwill, John H. Hitchcock, Rob Horner, Joel R. Levin, Robert H. Horner, C. Keith Haddock, Joel R. Sneed and Larry V. Hedges and has published in prestigious journals such as Psychological Bulletin, American Journal of Psychiatry and Biological Psychiatry.

In The Last Decade

David Rindskopf

89 papers receiving 5.3k citations

Hit Papers

Single-Case Designs Technical Documentation. 2010 2026 2015 2020 2010 2012 250 500 750 1000

Peers

David Rindskopf
John M. Ferron United States
James E. Pustejovsky United States
James E. Laughlin United States
David B. Pillemer United States
Jack L. Vevea United States
Mark I. Appelbaum United States
Daniel M. Bolt United States
S. Natasha Beretvas United States
Marley W. Watkins United States
Susan E. Embretson United States
John M. Ferron United States
David Rindskopf
Citations per year, relative to David Rindskopf David Rindskopf (= 1×) peers John M. Ferron

Countries citing papers authored by David Rindskopf

Since Specialization
Citations

This map shows the geographic impact of David Rindskopf'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 David Rindskopf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Rindskopf more than expected).

Fields of papers citing papers by David Rindskopf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Rindskopf. 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 David Rindskopf. The network helps show where David Rindskopf may publish in the future.

Co-authorship network of co-authors of David Rindskopf

This figure shows the co-authorship network connecting the top 25 collaborators of David Rindskopf. A scholar is included among the top collaborators of David Rindskopf 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 David Rindskopf. David Rindskopf 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.
Rindskopf, David, et al.. (2025). The Effect of White Matter Hyperintensity Burden on Antidepressant Treatment Remission: A Meta-Analysis. American Journal of Geriatric Psychiatry. 33(9). 947–961.
2.
Antonacci, Anthony C., Alexander E. Farrell, David Rindskopf, et al.. (2025). Optimizing Complication Self-Reporting Methodologies Improves Standard of Care and Quality. Journal of Surgical Research. 309. 277–287.
3.
Rindskopf, David, et al.. (2024). Using Concurrent Complication Reporting to Evaluate Resident Critical Thinking and Enhance Adult Learning. Journal of surgical education. 81(5). 702–712. 1 indexed citations
4.
Röver, Christian, David Rindskopf, & Tim Friede. (2023). How trace plots help interpret meta‐analysis results. Research Synthesis Methods. 15(3). 413–429. 3 indexed citations
5.
Patel, Vihas, et al.. (2022). Practice-Based Learning and Improvement: Improving Morbidity and Mortality Review Using Natural Language Processing. Journal of Surgical Research. 283. 351–356. 4 indexed citations
6.
Antonacci, Anthony C., et al.. (2021). Cognitive bias and severity of harm following surgery: Plan for workflow debiasing strategy. The American Journal of Surgery. 222(6). 1172–1177. 6 indexed citations
7.
Moeyaert, Mariola, David Rindskopf, Patrick Onghena, & Wim Van Den Noortgate. (2017). Multilevel modeling of single-case data: A comparison of maximum likelihood and Bayesian estimation.. Psychological Methods. 22(4). 760–778. 46 indexed citations
8.
Rindskopf, David. (2014). Nonlinear Bayesian analysis for single case designs. Journal of School Psychology. 52(2). 179–189. 40 indexed citations
9.
Rindskopf, David. (2013). Fully Bayesian Estimation of Data from Single Case Designs.. Society for Research on Educational Effectiveness. 1 indexed citations
10.
Rindskopf, David. (2013). Bayesian analysis of data from single case designs. Neuropsychological Rehabilitation. 24(3-4). 572–589. 14 indexed citations
11.
Shadish, William R., et al.. (2013). Analyzing data from single-case designs using multilevel models: New applications and some agenda items for future research.. Psychological Methods. 18(3). 385–405. 120 indexed citations
12.
Shadish, William R., Larry V. Hedges, James E. Pustejovsky, & David Rindskopf. (2012). A D-Estimator for Single-Case Designs.. Society for Research on Educational Effectiveness. 2 indexed citations
13.
Rindskopf, David, William R. Shadish, & Larry V. Hedges. (2012). A Simple Effect Size Estimator for Single Case Designs Using WinBUGS.. Society for Research on Educational Effectiveness. 5 indexed citations
14.
Shiyko, Mariya, Yuelin Li, & David Rindskopf. (2012). Poisson Growth Mixture Modeling of Intensive Longitudinal Data: An Application to Smoking Cessation Behavior. Structural Equation Modeling A Multidisciplinary Journal. 19(1). 65–85. 9 indexed citations
15.
Strauss, Shiela M., et al.. (2011). Enhancing Drug Treatment Program Staff's Self-Efficacy to Support Patients' HCV Needs. Journal of Social Work Practice in the Addictions. 11(3). 254–269. 3 indexed citations
16.
Rutherford, Bret R., et al.. (2011). Deconstructing Pediatric Depression Trials: An Analysis of the Effects of Expectancy and Therapeutic Contact. Journal of the American Academy of Child & Adolescent Psychiatry. 50(8). 782–795. 40 indexed citations
17.
Shadish, William R., et al.. (2009). Using UnGraph to extract data from image files: Verification of reliability and validity. Behavior Research Methods. 41(1). 177–183. 77 indexed citations
18.
Sneed, Joel R., David Rindskopf, David C. Steffens, Kousik Krishnan, & Steven P. Roose. (2008). The Vascular Depression Subtype: Evidence of Internal Validity. Biological Psychiatry. 64(6). 491–497. 88 indexed citations
19.
Sneed, Joel R., et al.. (2007). Design Makes a Difference: A Meta-Analysis of Antidepressant Response Rates in Placebo-Controlled Versus Comparator Trials in Late-Life Depression. American Journal of Geriatric Psychiatry. 16(1). 65–73. 110 indexed citations
20.
Strauss, Shiela M., et al.. (2005). Using latent class analysis to identify patterns of hepatitis C service provision in drug-free treatment programs in the U.S.. Drug and Alcohol Dependence. 83(1). 15–24. 12 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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