Jodi M. Casabianca
- Statistics and Probability top 5%
- Advanced Statistical Methods and Models 3
- Statistical Methods and Inference 2
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- Psychometric Methodologies and Testing 8
- Education top 10%
- School Choice and Performance 2
- Student Assessment and Feedback 2
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- Advanced Statistical Modeling Techniques 5
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- Reliability and Agreement in Measurement 4
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- Heart Rate Variability and Autonomic Control 1
- Co-authors
- Daniel F. McCaffreyJ. R. LockwoodLeah TuzzioJason WangJane E. SiskPaul L. HebertMary Ann McLaughlinRobert C. Pianta
- Cited by
- Statistics and ProbabilityInformation Systems and ManagementManagement Science and Operations Research
- Partner nations
- United StatesSwitzerlandSouth Korea
In The Last Decade
Jodi M. Casabianca
23 papers receiving 370 citations
Peers
Comparison fields: 5 of 71
- Statistics and Probability 54
- Information Systems and Management 45
- Management Science and Operations Research 68
- Education 136
- Family Practice 10
Countries citing papers authored by Jodi M. Casabianca
This map shows the geographic impact of Jodi M. Casabianca'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 Jodi M. Casabianca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jodi M. Casabianca more than expected).
Fields of papers citing papers by Jodi M. Casabianca
This network shows the impact of papers produced by Jodi M. Casabianca. 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 Jodi M. Casabianca. The network helps show where Jodi M. Casabianca may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jodi M. Casabianca, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2023 | 5 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 8 | |
| 5 | 2019 | 31 | |
| 6 | 2018 | 8 | |
| 7 | 2017 | 4 | |
| 8 | 2017 | 5 | |
| 9 | 2016 | 1 | |
| 10 | 2015 | 11 | |
| 11 | 2014 | 75 | |
| 12 | Rater Drift and Time Trends in Classroom Observations. | 2013 | 2 |
| 13 | 2013 | 59 | |
| 14 | 2011 | 50 | |
| 15 | Loglinear smoothing for the latent trait distribution: A two-tiered evaluation | 2011 | 2 |
| 16 | 2008 | 83 | |
| 17 | An Evaluation of the Kernel Equating Method: A Special Study with Pseudotests Constructed from Real Test Data. Research Report. ETS RR-06-02. | 2006 | 8 |
| 18 | 2006 | 22 | |
| 19 | 2004 | 2 | |
| 20 | 2004 | 4 |
About Jodi M. Casabianca
Jodi M. Casabianca is a scholar working on Statistics and Probability, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 24 papers that have together received 390 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (8 papers), Advanced Statistical Modeling Techniques (5 papers), Reliability and Agreement in Measurement (4 papers), Advanced Statistical Methods and Models (3 papers), Statistical Methods and Inference (2 papers), School Choice and Performance (2 papers), Student Assessment and Feedback (2 papers) and Heart Rate Variability and Autonomic Control (1 paper). The work is most often cited by research in Statistics and Probability (54 citations), Information Systems and Management (45 citations) and Management Science and Operations Research (68 citations). Jodi M. Casabianca has collaborated with scholars based in United States, Switzerland and South Korea. Frequent co-authors include Daniel F. McCaffrey, J. R. Lockwood, Leah Tuzzio, Jason Wang, Jane E. Sisk, Paul L. Hebert, Mary Ann McLaughlin, Robert C. Pianta, Carol R. Horowitz and Mark R. Chassin.
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.