Laura M. Stapleton

5.9k total citations · 4 hit papers
72 papers, 4.1k citations indexed

About

Laura M. Stapleton is a scholar working on Education, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, Laura M. Stapleton has authored 72 papers receiving a total of 4.1k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Education, 20 papers in Statistics and Probability and 17 papers in Management Science and Operations Research. Recurrent topics in Laura M. Stapleton's work include Statistical Methods and Bayesian Inference (14 papers), Psychometric Methodologies and Testing (13 papers) and Advanced Causal Inference Techniques (10 papers). Laura M. Stapleton is often cited by papers focused on Statistical Methods and Bayesian Inference (14 papers), Psychometric Methodologies and Testing (13 papers) and Advanced Causal Inference Techniques (10 papers). Laura M. Stapleton collaborates with scholars based in United States, Netherlands and Denmark. Laura M. Stapleton's co-authors include Daniel McNeish, Gregory R. Hancock, Keenan A. Pituch, Ralph O. Mueller, Ji Seung Yang, Richard G. Best, Ronald G. Downey, Marie‐Anne Suizzo, Tiffany A. Whittaker and Meredith L. Rowe and has published in prestigious journals such as Child Development, Review of Educational Research and Psychosomatic Medicine.

In The Last Decade

Laura M. Stapleton

70 papers receiving 3.9k citations

Hit Papers

align trajectories

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.

On the unnecessary ubiquity of hierarchical linear modeling.

2016 566 citations Daniel McNeish, Laura M. Stapleton et al. Psychological Methods profile →
The Effect of Small Sample Size on Two-Level Model Estimates: A Review and Illustration

2014 492 citations Daniel McNeish, Laura M. Stapleton Educational Psychology Review profile →
The Reviewer’s Guide to Quantitative Methods in the Social Sciences

2018 362 citations Laura M. Stapleton et al. profile →
Modeling Clustered Data with Very Few Clusters

2016 273 citations Daniel McNeish, Laura M. Stapleton Multivariate Behavioral Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Laura M. Stapleton United States	29	1.1k	886	759	686	556	72	4.1k
Robin K. Henson United States	29	1.7k 1.5×	1.3k 1.4×	1.1k 1.5×	789 1.2×	664 1.2×	92	6.0k
G. John Geldhof United States	29	1.0k 0.9×	1.1k 1.2×	925 1.2×	528 0.8×	666 1.2×	82	3.4k
Christine DiStefano United States	28	813 0.7×	1.1k 1.3×	1.3k 1.7×	758 1.1×	726 1.3×	90	4.3k
Cora J. M. Maas Netherlands	23	655 0.6×	1.1k 1.2×	993 1.3×	1.2k 1.7×	754 1.4×	40	5.5k
Tiffany A. Whittaker United States	22	1.1k 1.0×	1.2k 1.4×	1.1k 1.5×	1.0k 1.5×	551 1.0×	58	4.7k
John Tisak United States	25	677 0.6×	962 1.1×	1.1k 1.4×	585 0.9×	724 1.3×	55	3.4k
Lawrence M. Rudner United States	18	1.3k 1.2×	689 0.8×	623 0.8×	877 1.3×	379 0.7×	79	4.7k
James P. Byrnes United States	32	1.4k 1.3×	747 0.8×	556 0.7×	802 1.2×	904 1.6×	73	5.5k
Alexander Robitzsch Germany	32	1.7k 1.5×	1.4k 1.5×	759 1.0×	732 1.1×	1.3k 2.4×	171	5.5k
Rob R. Meijer Netherlands	40	522 0.5×	819 0.9×	1.0k 1.3×	522 0.8×	965 1.7×	162	5.4k

Countries citing papers authored by Laura M. Stapleton

Since Specialization

Citations

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

Fields of papers citing papers by Laura M. Stapleton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Laura M. Stapleton. 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 Laura M. Stapleton. The network helps show where Laura M. Stapleton may publish in the future.

Co-authorship network of co-authors of Laura M. Stapleton

This figure shows the co-authorship network connecting the top 25 collaborators of Laura M. Stapleton. A scholar is included among the top collaborators of Laura M. Stapleton 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 Laura M. Stapleton. Laura M. Stapleton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Killen, Melanie, et al.. (2024). Does intergroup contact increase children’s desire to play with diverse peers and reduce experiences of social exclusion?. Peace and Conflict Journal of Peace Psychology. 30(3). 413–425. 1 indexed citations

Henneberger, Angela K., et al.. (2023). Estimating Student Attrition in School-Based Prevention Studies: Guidance from State Longitudinal Data in Maryland. Prevention Science. 24(5). 1035–1045. 3 indexed citations

Killen, Melanie, et al.. (2022). Testing the effectiveness of the Developing Inclusive Youth program: A multisite randomized control trial. Child Development. 93(3). 732–750. 21 indexed citations

Feng, Yi, Angela K. Henneberger, Mark Lachowicz, et al.. (2019). The Promise and Limitations of Synthetic Data as a Strategy to Expand Access to State-Level Multi-Agency Longitudinal Data. Journal of Research on Educational Effectiveness. 12(4). 616–647. 24 indexed citations

Stapleton, Laura M., et al.. (2019). Models to Examine the Validity of Cluster-Level Factor Structure Using Individual-Level Data. Advances in Methods and Practices in Psychological Science. 2(3). 312–329. 14 indexed citations

Wexler, Jade, et al.. (2019). A Synthesis of Reading Comprehension Interventions for Persons With Mild Intellectual Disability. Review of Educational Research. 89(4). 612–651. 15 indexed citations

Stapleton, Laura M., et al.. (2019). Incidental Second-Level Dependence in Educational Survey Data with a Nested Data Structure. Educational Psychology Review. 31(3). 571–596. 2 indexed citations

Leite, Walter L., et al.. (2018). Propensity Score Analysis of Complex Survey Data with Structural Equation Modeling: A Tutorial with Mplus. Structural Equation Modeling A Multidisciplinary Journal. 26(3). 448–469. 13 indexed citations

McNeish, Daniel, et al.. (2016). On the unnecessary ubiquity of hierarchical linear modeling.. Psychological Methods. 22(1). 114–140. 566 indexed citations breakdown →

10.

McNeish, Daniel & Laura M. Stapleton. (2016). Modeling Clustered Data with Very Few Clusters. Multivariate Behavioral Research. 51(4). 495–518. 273 indexed citations breakdown →

11.

Stapleton, Laura M., et al.. (2016). Assessing the Workforce Outcomes of Maryland Science, Technology, Engineering, and Math (STEM) Postsecondary Graduates.. Grantee Submission.

12.

Bright, Charlotte Lyn, et al.. (2016). Gender Differences in Patterns of Substance Use and Delinquency: A Latent Transition Analysis. Journal of Child & Adolescent Substance Abuse. 26(2). 162–173. 21 indexed citations

13.

Leite, Walter L., et al.. (2015). An Evaluation of Weighting Methods Based on Propensity Scores to Reduce Selection Bias in Multilevel Observational Studies. Multivariate Behavioral Research. 50(3). 265–284. 38 indexed citations

14.

Stapleton, Laura M., Keenan A. Pituch, & Éric Dion. (2014). Standardized Effect Size Measures for Mediation Analysis in Cluster-Randomized Trials. The Journal of Experimental Education. 83(4). 547–582. 13 indexed citations

15.

Goodin, Burel R., Christopher D. King, Gayle G. Page, et al.. (2011). Salivary cortisol and soluble tumor necrosis factor‐α receptor II responses to multiple experimental modalities of acute pain. Psychophysiology. 49(1). 118–127. 34 indexed citations

16.

Schultz, David, et al.. (2010). Development of a Questionnaire Assessing Teacher Perceived Support for and Attitudes About Social and Emotional Learning. Early Education and Development. 21(6). 865–885. 14 indexed citations

17.

Goodin, Burel R., et al.. (2009). Pain Catastrophizing Mediates the Relationship Between Self-Reported Strenuous Exercise Involvement and Pain Ratings: Moderating Role of Anxiety Sensitivity. Psychosomatic Medicine. 71(9). 1018–1025. 24 indexed citations

18.

Stapleton, Laura M., Janay B. Sander, & Kevin D. Stark. (2007). Psychometric properties of the Beck Depression Inventory for Youth in a sample of girls.. Psychological Assessment. 19(2). 230–235. 31 indexed citations

19.

Fine, Jodene Goldenring, Margaret Semrud‐Clikeman, Timothy Z. Keith, Laura M. Stapleton, & George W. Hynd. (2007). Reading and the corpus callosum: An MRI family study of volume and area.. Neuropsychology. 21(2). 235–241. 33 indexed citations

20.

Best, Richard G., Laura M. Stapleton, & Ronald G. Downey. (2005). Core Self-Evaluations and Job Burnout: The Test of Alternative Models.. Journal of Occupational Health Psychology. 10(4). 441–451. 179 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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