What is he best known for?
The fields of study he is best known for:
- Statistics
- Internal medicine
- Law
Thomas D. Cook mainly focuses on Internal medicine, Epistemology, Econometrics, Heart failure and Meta-analysis.
The various areas that Thomas D. Cook examines in his Internal medicine study include Gastroenterology and Multiple sclerosis.
His work carried out in the field of Epistemology brings together such families of science as Replication crisis, p-value and Statistical significance.
His study in Econometrics is interdisciplinary in nature, drawing from both Regression analysis, Statistics, Randomized experiment and Artificial intelligence.
The Heart failure study combines topics in areas such as Heart disease, Surgery and Hazard ratio.
The study incorporates disciplines such as General knowledge, Phenomenon, Clinical psychology, Value and Casebook in addition to Meta-analysis.
His most cited work include:
- Quasi-Experimentation: Design & Analysis Issues for Field Settings (10549 citations)
- Experimental and Quasi-Experimental Designs for Generalized Causal Inference (8082 citations)
- Effects of Oral Tolvaptan in Patients Hospitalized for Worsening Heart Failure: The EVEREST Outcome Trial (1252 citations)
What are the main themes of his work throughout his whole career to date?
Thomas D. Cook spends much of his time researching Social psychology, Statistics, Econometrics, Internal medicine and Regression discontinuity design.
He has included themes like Developmental psychology and Cognitive psychology in his Social psychology study.
His study in Econometrics focuses on Causal inference in particular.
Specifically, his work in Internal medicine is concerned with the study of Heart failure.
His work on Ejection fraction and Tolvaptan as part of general Heart failure study is frequently linked to In patient, therefore connecting diverse disciplines of science.
Randomized experiment is closely attributed to Randomized controlled trial in his work.
He most often published in these fields:
- Social psychology (13.98%)
- Statistics (13.98%)
- Econometrics (13.04%)
What were the highlights of his more recent work (between 2015-2021)?
- Statistics (13.98%)
- Randomized controlled trial (7.45%)
- Internal medicine (10.56%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Statistics, Randomized controlled trial, Internal medicine, Econometrics and Cardiology.
The Randomized controlled trial study combines topics in areas such as Covariate, Evidence-based practice, Early childhood and Public health.
As part of one scientific family, he deals mainly with the area of Econometrics, narrowing it down to issues related to the Statistical significance, and often Epistemology, Replication crisis and p-value.
His Cardiology study combines topics from a wide range of disciplines, such as Surgery and Effects of sleep deprivation on cognitive performance, Cognition.
His Causal inference study integrates concerns from other disciplines, such as Matching, Internal validity and External validity.
The various areas that he examines in his External validity study include Construct validity, Statistical conclusion validity, Cognitive psychology, Meta-analysis and Bayesian probability.
Between 2015 and 2021, his most popular works were:
- Redefine statistical significance (993 citations)
- Redefine statistical significance (993 citations)
- Histopathologic Validation of Grayscale Carotid Plaque Characteristics Related to Plaque Vulnerability. (31 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Law
- Internal medicine
Econometrics, Statistics, Causal inference, Statistical significance and Selection are his primary areas of study.
His Statistics research focuses on Randomized experiment, External validity, Regression discontinuity design and Standard deviation.
Thomas D. Cook has researched Randomized experiment in several fields, including Matching, Covariate, Treatment and control groups, Test validity and Data set.
The concepts of his Causal inference study are interwoven with issues in Internal validity, Randomized controlled trial and Bayesian probability.
His Statistical significance research includes elements of Epistemology, p-value and Replication crisis.
His research in Selection intersects with topics in Observational study, Correlation, Outcome, Propensity score matching and Selection bias.
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