Karla Díaz-Ordaz

7.0k citations
51 papers · 1.5k indexed · 2 hit papers · h-index 18

Karla Díaz-Ordaz

50 papers receiving 1.5k citations

Hit Papers

Increased mortality in community-tested cases of SARS-CoV...5572021202620222024100200300400500

Peers

Karla Díaz-Ordaz
Comparison fields: 5 of 134
  • Infectious Diseases 646
  • Modeling and Simulation 148
  • Statistics and Probability 177
  • Health 180
  • Geriatrics and Gerontology 57
Replace Andrew Anglemyer with:
Andrew Anglemyer United States
Catherine R. Lesko United States
Milensu Shanyinde United Kingdom
David Benkeser United States
Mohammad Karamouzian Canada
Rafael Dal‐Ré Spain
Aman Verma Canada
Natasha K. Martin United States
Shahab Jolani Netherlands
Dale A. Rhoda United States
Karla Díaz-Ordaz relative to Andrew Anglemyer United States Andrew Anglemyer's profile →
Citations per field
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Andrew Anglemyer · 1×
Citations per year

Countries citing papers authored by Karla Díaz-Ordaz

Since Specialization
Citations

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

Fields of papers citing papers by Karla Díaz-Ordaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karla Díaz-Ordaz. 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 Karla Díaz-Ordaz. The network helps show where Karla Díaz-Ordaz may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20241
3 20241
4 20241
5 20242
6 20232
7 20237
8 20232
9 202117
10 202117
11
Risk prediction of covid-19 related death and hospital admission in adults after covid-19 vaccination: national prospective cohort studybreakdown →
2021196
12 20214
13 202147
14 20178
15 201689
16 20144
17 201436
18 201313
19 201338
20 201395

About Karla Díaz-Ordaz

Karla Díaz-Ordaz is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Economics and Econometrics, having authored 51 papers that have together received 1.5k indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (15 papers), Advanced Causal Inference Techniques (15 papers), Statistical Methods in Clinical Trials (9 papers), Statistical Methods and Bayesian Inference (9 papers), Meta-analysis and systematic reviews (7 papers), Mathematical Dynamics and Fractals (5 papers), Musculoskeletal pain and rehabilitation (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Infectious Diseases (646 citations), Modeling and Simulation (148 citations) and Statistics and Probability (177 citations). Karla Díaz-Ordaz has collaborated with scholars based in United Kingdom, United States and Belgium. Frequent co-authors include Ruth H. Keogh, Nicholas P. Jewell, Christopher I Jarvis, W. John Edmunds, Nicholas G. Davies, Sandra Eldridge, Michael G. Kenward, Richard Grieve, Martin Underwood and Bart Sheehan. Their work appears in journals such as Nature, The Lancet and SHILAP Revista de lepidopterología.

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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