Catharine B. Stack
- Pharmacology top 5%
- Physiology top 10%
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- Meta-analysis and systematic reviews 4
- Animal Science and Zoology top 5%
- Genetics top 10%
- BRCA gene mutations in cancer 3
- Genomics and Rare Diseases 2
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- Statistical Methods in Clinical Trials 6
- Advanced Causal Inference Techniques 3
- Statistical Methods and Bayesian Inference 1
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- Health Systems, Economic Evaluations, Quality of Life 4
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- Ethics in Clinical Research 1
- Co-authors
- Stephen B. LiggettKrishnan NandabalanJonathan StephensGualberto RuañoKevin ArnoldRichard JudsonDennis W. McGrawCynthia D. Mulrow
- Journals
- Annals of Internal Medicine (7 papers)Journal of Personalized Medicine (1 paper)Clinical Trials (1 paper)
- Partner nations
- United States
In The Last Decade
Catharine B. Stack
15 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Pharmacology 152
- Physiology 315
- Statistics, Probability and Uncertainty 65
- Animal Science and Zoology 93
- Genetics 253
Countries citing papers authored by Catharine B. Stack
This map shows the geographic impact of Catharine B. Stack'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 Catharine B. Stack with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Catharine B. Stack more than expected).
Fields of papers citing papers by Catharine B. Stack
This network shows the impact of papers produced by Catharine B. Stack. 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 Catharine B. Stack. The network helps show where Catharine B. Stack may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Catharine B. Stack, 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 | 2020 | 1 | |
| 2 | 2018 | 1 | |
| 3 | 2017 | 16 | |
| 4 | 2017 | 16 | |
| 5 | 2017 | 5 | |
| 6 | 2014 | 330 | |
| 7 | 2014 | 19 | |
| 8 | 2013 | 33 | |
| 9 | 2013 | 12 | |
| 10 | 2013 | 7 | |
| 11 | 2011 | 35 | |
| 12 | 2010 | 55 | |
| 13 | Complex promoter and coding region β 2 -adrenergic receptor haplotypes alter receptor expression and predict in vivo responsivenessbreakdown → | 2000 | 745 |
| 14 | 1995 | 23 | |
| 15 | 1995 | 24 |
About Catharine B. Stack
Catharine B. Stack is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Pharmacy, Economics and Econometrics and Genetics, having authored 15 papers that have together received 1.3k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (6 papers), Meta-analysis and systematic reviews (4 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), BRCA gene mutations in cancer (3 papers), Advanced Causal Inference Techniques (3 papers), Genomics and Rare Diseases (2 papers), Statistical Methods and Bayesian Inference (1 paper) and Ethics in Clinical Research (1 paper). The work is most often cited by research in Pharmacology (152 citations), Physiology (315 citations), Statistics, Probability and Uncertainty (65 citations), Animal Science and Zoology (93 citations) and Genetics (253 citations). Catharine B. Stack has collaborated with scholars based in United States. Frequent co-authors include Stephen B. Liggett, Krishnan Nandabalan, Jonathan Stephens, Gualberto Ruaño, Kevin Arnold, Richard Judson, Dennis W. McGraw, Cynthia D. Mulrow, John E. Cornell and Steven N. Goodman. Their work appears in journals such as Annals of Internal Medicine, Journal of Personalized Medicine, Clinical Trials, Genetics in Medicine and Statistical Methods in Medical Research.
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.