JAMA guide to statistics and methods
著者
書誌事項
JAMA guide to statistics and methods
McGraw-Hill Education, c2020
- [: pbk.]
- タイトル別名
-
Guide to statistics and methods
大学図書館所蔵 全6件
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.
The world-renowned experts at JAMA (R) explain statistical analysis and the methods used in medical research
Written in the language and style appropriate for clinicians and researchers, this new JAMA Guide to Statistics and Methods provides explanations and expert discussion of the statistical analytic approaches and methods used in the medical research reported in articles appearing in JAMA and the JAMA Network journals.
This addition to the JAMAevidence (R) series is particularly timely and necessary because today's physicians and other health care professionals must pursue lifelong learning to keep up with the ever-expanding universe of new medical science and evidence-based clinical information. Readers and users of research articles must have a firm grasp of the myriad new statistical, analytic, and methodologic approaches used in contemporary medical studies. To provide concrete examples, the explanations in the book link to research articles that incorporate the specific statistical test or methodological approach being discussed.
目次
Part I: Interventional Studies
Section I: Overall Trial Strategy
Noninferiority Trials
Does-Finding Trials
Pragmatic Trials
Cluster Randomized Trials
Section II: Clinical Trial Design
Samples Size Calculation for a Hypothesis Test
Minimal Clinically Importance Difference
Section III: Enrollment, Allocation of Treatment, Ethics
Randomization Strategies
Equipoise in Research
Section IV: Measurement of Outcome
Time-to-Event Analysis
Utility and Composite Outcomes
Missing Data
Section V:Analysis and Interpretation of Results
The Intention-to-Treat Principle
Analyzing Repeated Measurements/Mixed Models
Logistic Regression
Logistic Regression Diagnostics
Variable Selection in Regression
Multiple Comparison Procedures
Gatekeeping Strategies
Multiple Imputation
Interpretation of Clinical Trials that Stopped Early
Bayesian Modeling
Section VI: Application of Results
Decision Curve Analysis
Methods for Evaluating Changes in Health Care
Meta-Analysis Possible: Psychiatry VP loannidis
Part II: Observational Studies
Section I: Study Design
Case-Control Studies
Matched Case-Control Studies
Section II: Assessment of Risk Factors and Exposures
Mendelian Randomization
Confounding in Observational Studies
Confounding by Indication
Section III: Analysis and Interpretation of Results
The Propensity Score
Covariate Adjustment Possible
Instrumental Variable Matching
Genetic Association Studies
Section IV: Application of Results
Evaluation Discrimination of Risk Prediction Models
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