Ilya Lipkovich

2.8k total citations
90 papers, 1.8k citations indexed

About

Ilya Lipkovich is a scholar working on Statistics and Probability, Economics and Econometrics and Psychiatry and Mental health. According to data from OpenAlex, Ilya Lipkovich has authored 90 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Statistics and Probability, 23 papers in Economics and Econometrics and 19 papers in Psychiatry and Mental health. Recurrent topics in Ilya Lipkovich's work include Statistical Methods in Clinical Trials (39 papers), Advanced Causal Inference Techniques (38 papers) and Health Systems, Economic Evaluations, Quality of Life (22 papers). Ilya Lipkovich is often cited by papers focused on Statistical Methods in Clinical Trials (39 papers), Advanced Causal Inference Techniques (38 papers) and Health Systems, Economic Evaluations, Quality of Life (22 papers). Ilya Lipkovich collaborates with scholars based in United States, Belgium and United Kingdom. Ilya Lipkovich's co-authors include Alex Dmitrienko, Craig Mallinckrodt, Benjamin James Ralph, Bohdana Ratitch, Jonathan Denne, Gregory G. Enas, Geert Molenberghs, Eric P. Smith, Yongming Qu and Walter Deberdt and has published in prestigious journals such as PLoS ONE, Biometrika and Annals of the Rheumatic Diseases.

In The Last Decade

Ilya Lipkovich

85 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ilya Lipkovich United States	25	835	387	360	136	121	90	1.8k
Malka Gorfine Israel	24	324 0.4×	191 0.5×	121 0.3×	73 0.5×	135 1.1×	76	1.7k
Ying Kuen Cheung United States	28	1.1k 1.3×	191 0.5×	413 1.1×	218 1.6×	198 1.6×	114	2.5k
Mohammad F. Huque United States	16	507 0.6×	103 0.3×	232 0.6×	53 0.4×	89 0.7×	34	1.4k
Jonathan French United States	21	206 0.2×	218 0.6×	122 0.3×	216 1.6×	138 1.1×	74	2.0k
Roy Tamura United States	29	542 0.6×	692 1.8×	143 0.4×	69 0.5×	201 1.7×	82	2.7k
Kwun Chuen Gary Chan United States	23	329 0.4×	170 0.4×	97 0.3×	230 1.7×	205 1.7×	106	1.6k
Jaap Brand Netherlands	8	347 0.4×	60 0.2×	120 0.3×	161 1.2×	159 1.3×	11	1.4k
Mette T. Haahr Denmark	9	253 0.3×	89 0.2×	543 1.5×	133 1.0×	74 0.6×	10	1.9k
Karl E. Peace United States	20	398 0.5×	68 0.2×	150 0.4×	100 0.7×	105 0.9×	85	1.2k
Matheos Yosef United States	20	221 0.3×	65 0.2×	68 0.2×	246 1.8×	102 0.8×	49	2.1k

Countries citing papers authored by Ilya Lipkovich

Since Specialization

Citations

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

Fields of papers citing papers by Ilya Lipkovich

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ilya Lipkovich. 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 Ilya Lipkovich. The network helps show where Ilya Lipkovich may publish in the future.

Co-authorship network of co-authors of Ilya Lipkovich

This figure shows the co-authorship network connecting the top 25 collaborators of Ilya Lipkovich. A scholar is included among the top collaborators of Ilya Lipkovich 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 Ilya Lipkovich. Ilya Lipkovich 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

Done, Nicolae, Alan Brnabic, Ilya Lipkovich, et al.. (2026). Comparative effectiveness of tirzepatide and semaglutide for obesity management in US clinical practice: a 6-month retrospective cohort study. Journal of Endocrinological Investigation. 49(2). 413–423.

Brnabic, Alan, Ilya Lipkovich, Zbigniew Kadziola, et al.. (2025). Next-Generation Sequencing–Based Testing Among Patients With Advanced or Metastatic Nonsquamous Non–Small Cell Lung Cancer in the United States: Predictive Modeling Using Machine Learning Methods. JMIR Cancer. 11. e64399–e64399.

Choong, Casey, Beverly L. Falcón, Hong Kan, et al.. (2025). Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States. Diabetes Obesity and Metabolism. 27(6). 3061–3071.

Tan, Xiaoqing, Shu Yang, Wenyu Ye, et al.. (2025). Double machine learning methods for estimating average treatment effects: a comparative study. Journal of Biopharmaceutical Statistics. 35(6). 1176–1195.

Yang, Shu, et al.. (2024). Improving randomized controlled trial analysis via data-adaptive borrowing. Biometrika. 112(2). asae069–asae069. 1 indexed citations

Pinter, Andreas, Antonio Costanzo, Sanjay Khattri, et al.. (2023). Comparative Effectiveness and Durability of Biologics in Clinical Practice: Month 12 Outcomes from the International, Observational Psoriasis Study of Health Outcomes (PSoHO). Dermatology and Therapy. 14(6). 1479–1493. 8 indexed citations

Nowell, W. Benjamin, Jeffrey R. Curtis, Fenglong Xie, et al.. (2023). Participant Engagement and Adherence to Providing Smartwatch and Patient-Reported Outcome Data: Digital Tracking of Rheumatoid Arthritis Longitudinally (DIGITAL) Real-World Study. JMIR Human Factors. 10. e44034–e44034. 5 indexed citations

Turchin, Alexander, Fritha Morrison, Maria Shubina, et al.. (2023). EXIST: EXamining rIsk of excesS adiposiTy—Machine learning to predict obesity‐related complications. Obesity Science & Practice. 10(1). e707–e707. 4 indexed citations

Cui, Zhanglin Lin, Zbigniew Kadziola, Ilya Lipkovich, et al.. (2021). Predicting optimal treatment regimens for patients with HR+/HER2- breast cancer using machine learning based on electronic health records. Journal of Comparative Effectiveness Research. 10(9). 777–795. 6 indexed citations

10.

Yang, Shu, et al.. (2021). Practical recommendations on double score matching for estimating causal effects. Statistics in Medicine. 41(8). 1421–1445. 8 indexed citations

11.

Ratitch, Bohdana, Craig Mallinckrodt, Jonathan W. Bartlett, et al.. (2020). Choosing Estimands in Clinical Trials: Putting the ICH E9(R1) Into Practice. Therapeutic Innovation & Regulatory Science. 54(2). 324–341. 40 indexed citations

12.

Mallinckrodt, Craig, Bohdana Ratitch, Michael O’Kelly, et al.. (2020). Aligning Estimators With Estimands in Clinical Trials: Putting the ICH E9(R1) Guidelines Into Practice. Therapeutic Innovation & Regulatory Science. 54(2). 353–364. 42 indexed citations

13.

Ratitch, Bohdana, Craig Mallinckrodt, Jonathan W. Bartlett, et al.. (2019). Choosing Estimands in Clinical Trials: Putting the ICH E9(R1) Into Practice. Therapeutic Innovation & Regulatory Science. 3593143434–3593143434. 6 indexed citations

14.

Mallinckrodt, Craig, Bohdana Ratitch, Michael O’Kelly, et al.. (2019). Aligning Estimators With Estimands in Clinical Trials: Putting the ICH E9(R1) Guidelines Into Practice. Therapeutic Innovation & Regulatory Science. 3593143249–3593143249. 7 indexed citations

15.

Ratitch, Bohdana, Niti Goel, Craig Mallinckrodt, et al.. (2019). Defining Efficacy Estimands in Clinical Trials: Examples Illustrating ICH E9(R1) Guidelines. Therapeutic Innovation & Regulatory Science. 3593143683–3593143683. 3 indexed citations

16.

Lipkovich, Ilya, Alex Dmitrienko, Kaushik Patra, Bohdana Ratitch, & Erik Pulkstenis. (2017). Subgroup Identification in Clinical Trials by Stochastic SIDEScreen Methods. Statistics in Biopharmaceutical Research. 9(4). 368–378. 5 indexed citations

17.

Faries, Douglas E., Yi Chen, Ilya Lipkovich, et al.. (2013). Local control for identifying subgroups of interest in observational research: persistence of treatment for major depressive disorder. International Journal of Methods in Psychiatric Research. 22(3). 185–194. 13 indexed citations

18.

Severus, Emanuel, Ilya Lipkovich, Florian Seemüller, et al.. (2011). The potential role of Marginal Structural Models (MSMs) in testing the effectiveness of antidepressants in the treatment of patients with major depression in everyday clinical practice. The World Journal of Biological Psychiatry. 14(5). 386–395. 2 indexed citations

19.

Stauffer, Virginia L., et al.. (2009). Predictors and correlates for weight changes in patients co-treated with olanzapine and weight mitigating agents; a post-hoc analysis. BMC Psychiatry. 9(1). 12–12. 19 indexed citations

20.

Houston, John P., et al.. (2005). Initial symptoms of manic relapse in manic or mixed-manic bipolar disorder: Post hoc analysis of patients treated with olanzapine or lithium. Journal of Psychiatric Research. 41(7). 616–621. 14 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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