Robin Gomila

686 citations
6 papers · 357 indexed · 1 hit paper · h-index 5

Impact in

Papers in

Robin Gomila

6 papers receiving 350 citations

Hit Papers

Logistic or linear? Estimating causal effects of experimental treatments on binary outcomes using regression analysis. 2020 · 294 citations
294202020262022202450100150200250

Peers

Robin Gomila
Comparison fields: 5 of 110
  • Safety Research 37
  • Communication 23
  • Health 28
  • General Decision Sciences 6
  • Sociology and Political Science 141
Replace David McElhattan with:
David McElhattan United States
Hermann Dülmer Germany
Volker Stocké Germany
Melina Platas United States
Alessandra L. González United States
Maja Graso United States
Gigi Foster Australia
Kyle Peyton United States
Heather Laurie United Kingdom
Andrew Ward United Kingdom
Robin Gomila relative to David McElhattan United States David McElhattan's profile →
Citations per field
00.5×2.9×
David McElhattan · 1×
Citations per year

Countries citing papers authored by Robin Gomila

Since Specialization
Citations

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

Fields of papers citing papers by Robin Gomila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 9 scholars most cited alongside Robin Gomila, 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 Robin Gomila Line = papers co-authored together Robin Gomila links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1 202027
2
Logistic or linear? Estimating causal effects of experimental treatments on binary outcomes using regression analysis.
Hit paper breakdown →
2020294
3 20204
4 202011
5 20175
6 201516

About Robin Gomila

Robin Gomila is a scholar working on Applied Psychology, Literature and Literary Theory, Communication, Statistics and Probability and Management, Monitoring, Policy and Law, having authored 6 papers that have together received 357 indexed citations. Recurring topics across this work include Behavioral Health and Interventions (2 papers), Media Influence and Health (2 papers), Social and Intergroup Psychology (2 papers), Statistical Methods and Bayesian Inference (1 paper), Media Influence and Politics (1 paper), Survey Methodology and Nonresponse (1 paper), Advanced Causal Inference Techniques (1 paper) and Environmental Education and Sustainability (1 paper). The work is most often cited by research in Safety Research (37 citations), Communication (23 citations), Health (28 citations), General Decision Sciences (6 citations) and Sociology and Political Science (141 citations). Robin Gomila has collaborated with scholars based in United States. Frequent co-authors include Chelsey S. Clark, Elizabeth Levy Paluck, Paul Lagunes, Lynn Vavreck, Limor Peer, Donald P. Green, Hana Shepherd, Graeme Blair and Rebecca Littman. Their work appears in journals such as Psychological Methods, Journal of Social and Political Psychology, PLoS ONE, Social Psychological and Personality Science and Journal of Experimental Psychology General.

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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