Matteo Quartagno

2.1k citations
39 papers · 715 · h-index 14

Impact in

Papers in

    • Statistical Methods and Bayesian Inference 13
    • Statistical Methods in Clinical Trials 11
    • Advanced Causal Inference Techniques 8
    • Statistical Methods and Inference 4
    • Health Systems, Economic Evaluations, Quality of Life 6

Matteo Quartagno

34 papers receiving 709 citations

Peers

Matteo Quartagno
Comparison fields: 5 of 114
  • Statistics and Probability 193
  • Statistics, Probability and Uncertainty 57
  • Pediatrics, Perinatology and Child Health 90
  • Oncology 123
  • Biological Psychiatry 11
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Citations per field
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Citations per year

Countries citing papers authored by Matteo Quartagno

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Quartagno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202096
2 201891
3 201991
4 201557
5 202154
6 202037
7 201934
8 201930
9 201929
10 202328
11 202026
12 201819
13 202013
14 202313
15 202212
16 201910
17
jomo: Multilevel Joint Modelling Multiple Imputation
201610
18 20239
19 20217
20 20236

About Matteo Quartagno

Matteo Quartagno is a scholar working on Statistics and Probability, Economics and Econometrics, Oncology, Pediatrics, Perinatology and Child Health and Statistics, Probability and Uncertainty, having authored 39 papers that have together received 715 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (13 papers), Statistical Methods in Clinical Trials (11 papers), Advanced Causal Inference Techniques (8 papers), Health Systems, Economic Evaluations, Quality of Life (6 papers), Meta-analysis and systematic reviews (5 papers), Statistical Methods and Inference (4 papers), Cancer Immunotherapy and Biomarkers (4 papers) and Obesity, Physical Activity, Diet (3 papers). The work is most often cited by research in Statistics and Probability (193 citations), Statistics, Probability and Uncertainty (57 citations), Pediatrics, Perinatology and Child Health (90 citations), Oncology (123 citations) and Biological Psychiatry (11 citations). Matteo Quartagno has collaborated with scholars based in United Kingdom, Kenya and Netherlands. Frequent co-authors include James R. Carpenter, Simon Grund, Ian R. White, Shahab Jolani, Harvey Goldstein, Stef van Buuren, Thomas P. A. Debray, Vincent Audigier, Matthieu Resche‐Rigon and Jane Walker. Their work appears in journals such as Statistics in Medicine, The Lancet Oncology, Biometrical Journal, Contemporary Clinical Trials and Clinical Trials.

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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