Miguel A. Hernán

123.3k citations
313 papers · 42.2k · 28 hit papers · h-index 93

Impact in

    • Advanced Causal Inference Techniques
    • Statistical Methods in Clinical Trials
    • Statistical Methods and Inference
    • Statistical Methods and Bayesian Inference
  • Health top 0.05%

Papers in

    • Advanced Causal Inference Techniques 117
    • Statistical Methods and Inference 47
    • Statistical Methods in Clinical Trials 42
    • Statistical Methods and Bayesian Inference 37
    • Health Systems, Economic Evaluations, Quality of Life 62

Miguel A. Hernán

307 papers receiving 40.9k citations

Miguel A. Hernán's Hit Papers

The Target Trial Framework for Causal Inference From Observational Data: Why and When Is It Helpful? 2025 · 23 citations
230+6+12Years since publication50010001.5k

Peers

Miguel A. Hernán
Comparison fields: 5 of 215
  • Statistics and Probability 9.2k
  • Health 2.9k
  • Infectious Diseases 5.8k
  • Pathology and Forensic Medicine 4.2k
  • Neurology 3.3k
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Citations per field
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Citations per year

Countries citing papers authored by Miguel A. Hernán

Since Specialization
Citations

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

Fields of papers citing papers by Miguel A. Hernán

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miguel A. Hernán. 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 Miguel A. Hernán. The network helps show where Miguel A. Hernán may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 313 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Marginal Structural Models and Causal Inference in Epidemiology
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20003871
2
Constructing Inverse Probability Weights for Marginal Structural Models
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20081935
3
A Structural Approach to Selection Bias
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20041852
4
BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Mass Vaccination Setting
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20211619
5
Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available: Table 1.
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20161505
6
Marginal Structural Models to Estimate the Causal Effect of Zidovudine on the Survival of HIV-Positive Men
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20001348
7
Causal Knowledge as a Prerequisite for Confounding Evaluation: An Application to Birth Defects Epidemiology
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20021069
8
The Hazards of Hazard Ratios
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2009872
9
Methotrexate and mortality in patients with rheumatoid arthritis: a prospective study
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2002835
10
Vitamin D intake and incidence of multiple sclerosis
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2004808
11
Estimating causal effects from epidemiological data
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2006695
12
Safety of the BNT162b2 mRNA Covid-19 Vaccine in a Nationwide Setting
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2021672
13
Instruments for Causal Inference
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2006638
14
Adjusted survival curves with inverse probability weights
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2003611
15
A meta‐analysis of coffee drinking, cigarette smoking, and the risk of Parkinson's disease
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2002601
16
Activated Injectable Vitamin D and Hemodialysis Survival
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2005589
17
Effectiveness of a third dose of the BNT162b2 mRNA COVID-19 vaccine for preventing severe outcomes in Israel: an observational study
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2021558
18
Observational Studies Analyzed Like Randomized Experiments
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2008556
19
Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses
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2016556
20
Prospective study of caffeine consumption and risk of Parkinson's disease in men and women
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2001527

About Miguel A. Hernán

Miguel A. Hernán is a scholar working on Statistics and Probability, Economics and Econometrics, Infectious Diseases, Oncology and Pathology and Forensic Medicine, having authored 313 papers that have together received 42.2k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (117 papers), Health Systems, Economic Evaluations, Quality of Life (62 papers), Statistical Methods and Inference (47 papers), Statistical Methods in Clinical Trials (42 papers), Statistical Methods and Bayesian Inference (37 papers), SARS-CoV-2 and COVID-19 Research (21 papers), HIV/AIDS Research and Interventions (19 papers) and Multiple Sclerosis Research Studies (19 papers). The work is most often cited by research in Statistics and Probability (9.2k citations), Health (2.9k citations), Infectious Diseases (5.8k citations), Pathology and Forensic Medicine (4.2k citations) and Neurology (3.3k citations). Miguel A. Hernán has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include James M. Robins, Babette Brumback, Stephen R. Cole, Sonia Hernández–Dı́az, Alberto Ascherio, Álvaro Alonso, Walter C. Willett, Michael J. Olek, Marc Lipsitch and Shumin M. Zhang. Their work appears in journals such as Epidemiology, American Journal of Epidemiology, European Journal of Epidemiology, Neurology and International Journal of Epidemiology.

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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