Alyssa Bilinski

3.5k citations
36 papers · 1.7k indexed · 1 hit paper · h-index 17

Impact in

Papers in

Alyssa Bilinski

34 papers receiving 1.6k citations

Hit Papers

What’s trending in difference-in-differences? A synthesis of the recent econometrics literature 2023 · 674 citations
6742023202620242025200400600

Peers

Alyssa Bilinski
Comparison fields: 5 of 137
  • Modeling and Simulation 257
  • Health 207
  • Economics and Econometrics 479
  • Infectious Diseases 318
  • Virology 79
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Citations per field
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Citations per year

Countries citing papers authored by Alyssa Bilinski

Since Specialization
Citations

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

Fields of papers citing papers by Alyssa Bilinski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Alyssa Bilinski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alyssa Bilinski Line = papers co-authored together Alyssa Bilinski links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3
What’s trending in difference-in-differences? A synthesis of the recent econometrics literature
Hit paper breakdown →
2023674
4 20235
5 20238
6 20235
7 20230
8 202224
9 20225
10 202212
11 202192
12 2020149
13
Seeking evidence of absence: Reconsidering tests of model assumptions
20188
14 201848
15 201833
16 201746
17 201766
18 201665
19 201651
20 201217

About Alyssa Bilinski

Alyssa Bilinski is a scholar working on Modeling and Simulation, Infectious Diseases, Virology, Epidemiology and Economics and Econometrics, having authored 36 papers that have together received 1.7k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (13 papers), Health Systems, Economic Evaluations, Quality of Life (5 papers), Viral Infections and Outbreaks Research (4 papers), Healthcare Policy and Management (4 papers), Virology and Viral Diseases (3 papers), COVID-19 and Mental Health (3 papers), Data-Driven Disease Surveillance (3 papers) and Healthcare cost, quality, practices (3 papers). The work is most often cited by research in Modeling and Simulation (257 citations), Health (207 citations), Economics and Econometrics (479 citations), Infectious Diseases (318 citations) and Virology (79 citations). Alyssa Bilinski has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include John Poe, Jonathan Roth, Pedro H. C. Sant’Anna, Ezekiel Emanuel, Joshua A. Salomon, Adam L. Beckman, Ishani Ganguli, Suhas Gondi, Rohan Khazanchi and Meagan C. Fitzpatrick. Their work appears in journals such as JAMA Network Open, Annals of Internal Medicine, Proceedings of the National Academy of Sciences, JAMA and JAMA Pediatrics.

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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