Sylva H. Collins

541 total citations
8 papers, 409 citations indexed

About

Sylva H. Collins is a scholar working on Statistics and Probability, Economics and Econometrics and Pharmacology. According to data from OpenAlex, Sylva H. Collins has authored 8 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistics and Probability, 4 papers in Economics and Econometrics and 2 papers in Pharmacology. Recurrent topics in Sylva H. Collins's work include Statistical Methods in Clinical Trials (5 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers) and Advanced Causal Inference Techniques (3 papers). Sylva H. Collins is often cited by papers focused on Statistical Methods in Clinical Trials (5 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers) and Advanced Causal Inference Techniques (3 papers). Sylva H. Collins collaborates with scholars based in United States, Switzerland and Austria. Sylva H. Collins's co-authors include Joseph S. Solomkin, Myra W. Popejoy, Guojun Yuan, Ian R. Friedland, Christian Eckmann, Philip S. Barie, Judith N. Steenbergen, Minjung Yoon, Benjamin Miller and Ellie Hershberger and has published in prestigious journals such as Clinical Infectious Diseases, Antimicrobial Agents and Chemotherapy and Statistics in Medicine.

In The Last Decade

Sylva H. Collins

7 papers receiving 405 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sylva H. Collins United States	5	242	215	174	137	93	8	409
Lucie Seyler Belgium	11	161 0.7×	369 1.7×	201 1.2×	150 1.1×	103 1.1×	22	552
Kathryn J. Eagye United States	14	189 0.8×	196 0.9×	142 0.8×	138 1.0×	38 0.4×	25	452
Myra W. Popejoy United States	11	431 1.8×	396 1.8×	250 1.4×	228 1.7×	90 1.0×	20	620
Abel Jasovich Argentina	10	202 0.8×	226 1.1×	211 1.2×	89 0.6×	76 0.8×	22	439
Julie Varghese Australia	8	160 0.7×	463 2.2×	244 1.4×	132 1.0×	63 0.7×	12	575
Ariadna Padullés Spain	11	174 0.7×	213 1.0×	227 1.3×	86 0.6×	84 0.9×	49	560
Jean Li Yan United States	13	234 1.0×	238 1.1×	226 1.3×	74 0.5×	198 2.1×	28	546
Abdulaziz S. Alobaid Australia	12	157 0.6×	330 1.5×	213 1.2×	115 0.8×	58 0.6×	12	463
Janattul‐Ain Jamal Australia	10	198 0.8×	511 2.4×	289 1.7×	154 1.1×	64 0.7×	12	592
Csaba Fehér Spain	14	180 0.7×	157 0.7×	190 1.1×	104 0.8×	119 1.3×	23	482

Countries citing papers authored by Sylva H. Collins

Since Specialization

Citations

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

Fields of papers citing papers by Sylva H. Collins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sylva H. Collins. 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 Sylva H. Collins. The network helps show where Sylva H. Collins may publish in the future.

Co-authorship network of co-authors of Sylva H. Collins

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

All Works

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8 of 8 papers shown

Fleming, Thomas R., Kevin J. Carroll, Janet Wittes, et al.. (2025). A Perspective on the Appropriate Implementation of ICH E9(R1) Addendum Strategies for Handling Intercurrent Events. Statistics in Medicine. 44(10-12). e70104–e70104.

Ionan, Alexei, Devan V. Mehrotra, John Scott, et al.. (2022). Clinical and Statistical Perspectives on the ICH E9(R1) Estimand Framework Implementation. Statistics in Biopharmaceutical Research. 15(3). 554–559. 5 indexed citations

Gwise, Thomas, Mark D. Rothmann, Hung Hung, et al.. (2021). Statement on P-values. Statistics in Biopharmaceutical Research. 13(1). 57–58. 1 indexed citations

Collins, Sylva H. & Mark Levenson. (2020). Comment on “Statistical Issues and Recommendations for Clinical Trials Conducted During the COVID-19 Pandemic”. Statistics in Biopharmaceutical Research. 12(4). 412–413. 4 indexed citations

Collins, Sylva H., et al.. (2020). The Role of FDA CDER Statisticians in Response Efforts to the COVID-19 Pandemic. Statistics in Biopharmaceutical Research. 14(1). 3–4. 1 indexed citations

Solomkin, Joseph S., Ellie Hershberger, Benjamin Miller, et al.. (2015). Ceftolozane/Tazobactam Plus Metronidazole for Complicated Intra-abdominal Infections in an Era of Multidrug Resistance: Results From a Randomized, Double-Blind, Phase 3 Trial (ASPECT-cIAI). Clinical Infectious Diseases. 60(10). 1462–1471. 311 indexed citations

D’Agostino, Ralph B., Sylva H. Collins, Karol M. Pencina, Yin Kean, & Sherwood L. Gorbach. (2014). Risk Estimation for Recurrent Clostridium difficile Infection Based on Clinical Factors. Clinical Infectious Diseases. 58(10). 1386–1393. 65 indexed citations

Harrison, Lester I., et al.. (1984). Determination of flumequine and a hydroxy metabolite in biological fluids by high-pressure liquid chromatographic, fluorometric, and microbiological methods. Antimicrobial Agents and Chemotherapy. 25(3). 301–305. 22 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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