What is he best known for?
The fields of study he is best known for:
- Statistics
- Internal medicine
- Cancer
His main research concerns Internal medicine, Confidence interval, Acquired immunodeficiency syndrome, Cohort study and Confounding.
His Internal medicine research incorporates elements of Surgery and Immunology.
His Confidence interval research is multidisciplinary, relying on both Odds ratio, Randomized controlled trial, Survival analysis and Depression.
The various areas that he examines in his Acquired immunodeficiency syndrome study include Mortality rate and Pediatrics.
The study incorporates disciplines such as Creatinine, Kidney disease and Renal function in addition to Cohort study.
His studies in Confounding integrate themes in fields like Causal inference and Selection bias.
His most cited work include:
- Constructing Inverse Probability Weights for Marginal Structural Models (1377 citations)
- Overadjustment bias and unnecessary adjustment in epidemiologic studies. (1040 citations)
- Fruit and vegetable intake and risk of cardiovascular disease: the Women's Health Study (789 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Internal medicine, Confidence interval, Statistics, Acquired immunodeficiency syndrome and Cohort study.
He has included themes like Surgery and Immunology in his Internal medicine study.
His Confidence interval study combines topics in areas such as Odds ratio, Demography, Pediatrics and Confounding.
Stephen R. Cole frequently studies issues relating to Econometrics and Statistics.
His Acquired immunodeficiency syndrome research includes elements of Epidemiology, Viral load and Gerontology.
His research integrates issues of Relative risk and Mortality rate in his study of Cohort study.
He most often published in these fields:
- Internal medicine (30.47%)
- Confidence interval (26.82%)
- Statistics (20.31%)
What were the highlights of his more recent work (between 2016-2021)?
- Internal medicine (30.47%)
- Confidence interval (26.82%)
- Statistics (20.31%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Internal medicine, Confidence interval, Statistics, Estimator and Randomized controlled trial.
His work deals with themes such as Efavirenz and Viral load, which intersect with Internal medicine.
His work carried out in the field of Viral load brings together such families of science as Adverse effect, Prospective cohort study, Pharmacotherapy and Acquired immunodeficiency syndrome.
The Confidence interval study combines topics in areas such as Public health and Antiretroviral therapy.
His Covariate study deals with Confounding intersecting with Relative risk.
His Hazard ratio study combines topics from a wide range of disciplines, such as Physical therapy, Proportional hazards model, Disease and Cohort.
Between 2016 and 2021, his most popular works were:
- Generalizing Study Results: A Potential Outcomes Perspective (96 citations)
- Transportability of Trial Results Using Inverse Odds of Sampling Weights. (92 citations)
- Empirical Comparison of Publication Bias Tests in Meta-Analysis (52 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Internal medicine
- Cancer
His scientific interests lie mostly in Internal medicine, Randomized controlled trial, Generalizability theory, Cohort study and Cohort.
His Confidence interval, Cumulative incidence, Hazard ratio, Survival analysis and Epidemiology investigations are all subjects of Internal medicine research.
Stephen R. Cole studies Absolute risk reduction which is a part of Confidence interval.
His research investigates the connection between Generalizability theory and topics such as External validity that intersect with problems in Internal validity, Econometrics and Causal inference.
He interconnects Viral load and Risk factor in the investigation of issues within Cohort study.
He combines subjects such as Marginal structural model, Mortality rate, Psychiatry, Depression and Lower risk with his study of Cohort.
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