2026 Jason W. Osborne: Social Sciences and Humanities Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Social Sciences and Humanities	44	3964	3659	1879	1702	108	36904

Overview

Jason W. Osborne is affiliated with Miami University in the United States. Their research output includes a number of papers published primarily through Scholarworks at the University of Massachusetts Amherst, with several contributions in other venues such as Nursing Practice Today, BMC Psychology, Annals of Clinical Biochemistry International Journal of Laboratory Medicine, and Frontiers in Psychology.

The scientist's notable recent publications include:

Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis (2020) published in Scholarworks (University of Massachusetts Amherst)
Improving your data transformations: Applying the Box-Cox transformation (2020) published in Scholarworks (University of Massachusetts Amherst)
The power of outliers (and why researchers should ALWAYS check for them) (2020) published in Scholarworks (University of Massachusetts Amherst)
Sample size and subject to item ratio in principal components analysis (2020) published in Scholarworks (University of Massachusetts Amherst)
Notes on the use of data transformations (2020) published in Scholarworks (University of Massachusetts Amherst)

Their frequent collaborators include Hamid Sharif Nia, Erika Sivarajan Froelicher, Özkan Görgülü, Fatemeh Khoshnavay Fomani, and Poorya Nowrozi.

Jason W. Osborne's research spans multiple fields and subfields, notably:

Statistics and Probability
Clinical Psychology
Management Science and Operations Research
Social Psychology
Materials Chemistry

Topics covered in their work reflect a focus on advanced statistical methods and their applications, including:

Advanced Statistical Methods and Models
Psychometric Methodologies and Testing
Advanced Statistical Modeling Techniques
Cognitive Abilities and Testing
Statistical Methods and Bayesian Inference
Diverse Scientific and Engineering Research
Musculoskeletal pain and rehabilitation

The publication venues with recurrent appearances of their work include:

Scholarworks (University of Massachusetts Amherst)
Nursing Practice Today
BMC Psychology
Annals of Clinical Biochemistry International Journal of Laboratory Medicine
Frontiers in Psychology

Jason W. Osborne's contributions largely concentrate on exploratory factor analysis, data transformations, outlier effects, and sample size considerations in statistical analyses. Their body of work embraces both statistical methodology and its relevance to psychological and clinical research contexts.

Best Publications

Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis.

Anna B. Costello;Jason Osborne

16952
Citations
Best Practices in Exploratory Factor Analysis: Four Recommendations for Getting the Most from Your Analysis

Jason W. Osborne;Anna B. Costello

2911
Citations
The power of outliers (and why researchers should ALWAYS check for them)

Jason W. Osborne;Amy Overbay

1533
Citations
Best Practices in Quantitative Methods

Jason W. Osborne

1430
Citations
Improving your data transformations: Applying the Box-Cox transformation

Jason W. Osborne

1312
Citations
Sample size and subject to item ratio in principal components analysis.

Jason W. Osborne;Anna B. Costello

1308
Citations
Notes on the use of data transformations.

Jason W. Osborne

1005
Citations
Best Practices in Exploratory Factor Analysis

Jason W. Osborne

914
Citations
Race and Academic Disidentification

Jason W. Osborne

751
Citations
Is inquiry possible in light of accountability?: A quantitative comparison of the relative effectiveness of guided inquiry and verification laboratory instruction

Margaret R. Blanchard;Sherry A. Southerland;Jason W. Osborne;Victor D. Sampson

631
Citations
Testing Stereotype Threat: Does Anxiety Explain Race and Sex Differences in Achievement?

Jason W. Osborne

585
Citations
Advantages of Hierarchical Linear Modeling.

Jason W. Osborne

542
Citations
Academics, Self-Esteem, and Race: A Look at the Underlying Assumptions of the Disidentification Hypothesis:

Jason W. Osborne

469
Citations
The Development of the STEM Career Interest Survey (STEM-CIS)

Meredith W. Kier;Margaret R. Blanchard;Jason W. Osborne;Jennifer L. Albert

462
Citations
Best Practices in Logistic Regression

Jason W. Osborne

434
Citations
Metacognitive Monitoring Accuracy and Student Performance in the Postsecondary Classroom.

John L. Nietfeld;Li Cao;Jason W. Osborne

421
Citations
Replication Analysis in Exploratory Factor Analysis: What it is and why it makes your analysis better

Jason W. Osborne;David C. Fitzpatrick

380
Citations
The effect of distributed monitoring exercises and feedback on performance, monitoring accuracy, and self-efficacy

John L. Nietfeld;Li Cao;Jason W. Osborne

368
Citations
Best Practices in Data Cleaning: A Complete Guide to Everything You Need to Do Before and After Collecting Your Data

Jason W. Osborne

346
Citations
Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

David B. Flora;Cathy LaBrish;R. Philip Chalmers

308
Citations

Frequent Co-Authors

Gordon J.G. Asmundson University of Regina

R. Nicholas Carleton University of Regina

Steven Taylor University of British Columbia

Peter Gallagher Newcastle University

Dennis M. McInerney Education University of Hong Kong

Carolyn B. Mervis University of Louisville

Sherry A. Southerland Florida State University

External Links

Personal website of Jason W. Osborne

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