Mette Gerster

459 citations
17 papers · 338 · h-index 9

Impact in

    • Statistical Methods and Inference
    • Advanced Causal Inference Techniques
    • Statistical Methods in Clinical Trials
    • Statistical Methods and Bayesian Inference
  • Demography top 10%
    • Family Dynamics and Relationships

Papers in

Mette Gerster

17 papers receiving 325 citations

Peers

Mette Gerster
Comparison fields: 5 of 69
  • Statistics and Probability 96
  • Demography 56
  • Medical Laboratory Technology 7
  • Gender Studies 34
  • Health 27
Replace Janet Pregler with:
Janet Pregler United States
Per‐Henrik Zahl Norway
Anastasia Kostaki Greece
Caroline B. Burnett United States
Viviana Egidi Italy
Marisol Rodrı́guez Spain
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Mette Gerster relative to Janet Pregler United States Janet Pregler's profile →
Citations per field
00.5×9.3×
Janet Pregler · 1×
Citations per year

Countries citing papers authored by Mette Gerster

Since Specialization
Citations

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

Fields of papers citing papers by Mette Gerster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mette Gerster, 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 Mette Gerster Line = papers co-authored together Mette Gerster links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 200896
2 201145
3 200745
4 201136
5 201235
6 201425
7 201312
8 201111
9 20138
10 20108
11 20117
12 20133
13 20073
14 20081
15 20111
16
Socioeconomic determinants for fertility
20091
17
Computes Pseudo-Observations for Modeling [R package pseudo version 1.4.3]
20171

About Mette Gerster

Mette Gerster is a scholar working on Demography, Pediatrics, Perinatology and Child Health, Sociology and Political Science, Statistics and Probability and Health, having authored 17 papers that have together received 338 indexed citations. Recurring topics across this work include Birth, Development, and Health (5 papers), Family Dynamics and Relationships (5 papers), Intergenerational Family Dynamics and Caregiving (3 papers), Statistical Methods and Bayesian Inference (3 papers), Statistical Methods and Inference (3 papers), Gender, Labor, and Family Dynamics (2 papers), BRCA gene mutations in cancer (2 papers) and Health disparities and outcomes (2 papers). The work is most often cited by research in Statistics and Probability (96 citations), Demography (56 citations), Medical Laboratory Technology (7 citations), Gender Studies (34 citations) and Health (27 citations). Mette Gerster has collaborated with scholars based in Denmark, United States and Belgium. Frequent co-authors include Per Kragh Andersen, Maja Pohar Perme, John P. Klein, Sergey Tarima, Niels Keiding, Lisbeth B. Knudsen, Anne‐Marie Nybo Andersen, Katrine Strandberg‐Larsen, Jacob Hjelmborg and Stijn Vansteelandt. Their work appears in journals such as Demographic Research, British Journal of Cancer, BMJ Open, International Archives of Occupational and Environmental Health and Scandinavian Journal of Public Health.

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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