Clinical epidemiology & evidence-based medicine : fundamental principles of clinical reasoning & research /

Written as a reference tool and resource for health care professionals, David L. Katz's primer uses clinical examples and extracts from peer-reviewed literature to show how statistical principles can improve medical decision making.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Katz, David L., 1963- (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Thousand Oaks, Calif. : Sage Publications, ©2001.
Temas:
Clinical epidemiology.
Evidence-based medicine.
Epidemiologic Methods
Épidémiologie clinique.
Médecine factuelle.
MEDICAL > Epidemiology.
MEDICAL > Health Risk Assessment.
Clinical epidemiology
Evidence-based medicine
Epidemiologie
Evidenz-basierte Medizin
Epidemiologie.
Evidence-based practice.
Psychology.
Health psychology.
Epidemiology & medical statistics.
Clinical & internal medicine.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Principles of Clinical Reasoning
  • Of Patients and Populations: Population-Based Data in Clinical Practice
  • Test Performance: Disease Probability, Test Interpretation and Diagnosis
  • Test Performance
  • Disease Probability
  • Test Interpretation
  • Quantitative Aspects of Clinical Thinking: Predictive Values and Bayes' Theorem
  • Application
  • Alternative Applications
  • Odds and Probabilities: Bayes' Theorem and Likelihood Ratios
  • Implications of Bayes' Theorem for Diagnostic Testing
  • Conceptual Factors Influencing Probability Estimates
  • Bayes' Theorem and the Sequence of Testing
  • Fundamentals of Screening: The Art and Science of Looking for Trouble
  • Screening Defined
  • Screening Criteria
  • Statistical Considerations Pertinent to Screening
  • Sequential Testing
  • Statistics, Screening and Monetary Costs
  • Statistics, Screening and Human Costs
  • Screening Pros and Cons
  • Measuring and Conveying Risk
  • Measuring Risk to the Individual Patient
  • Risk Factors
  • Measuring Risk in Clinical Investigation
  • Measuring Risk Modification
  • Principles of Clinical Research
  • Hypothesis Testing 1: Principles
  • Association
  • Variation
  • Measuring Central Tendency: The Mean
  • Measuring Dispersion: Variance and Standard Deviation
  • Testing Hypotheses: The Signal to Noise Ratio
  • Types of Clinical Data
  • Characterizing Associations: Univariate, Bivariate, and Multivariate Methods
  • Eliminating Alternative Explanations: The Threat of Confounding and Bias
  • Hypothesis Testing 2: Mechanics
  • Parametric Methods.

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