Statistical methods for drug safety
By: Robert D. Gibbons, University of Chicago, Illinos, USA, Anup K. Amatya, New Mexio State University, Las Cruces, USA
Contributors: Amatya, Anup K., author
Series: Chapman & Hall/CRC biostatistics series; Chapman & Hall/CRC biostatistics series (Unnumbered)
Publisher: CRC Press, Taylor & Francis Group; CRC Press; Chapman and Hall/CRC
Published: 2016
Place of publication: Boca Raton, FL
Language: eng
Number of pages: 288
ISBN-13: 9781466561847
Subjects: Pharmacoepidemiology; Statistical methods; Safety measures; Methods; Statistics as Topic; Drugs; Pharmacovigilance
Notes: "A Chapman & Hall book."

Includes bibliographical references (page 255-273) and index.
Table of contents: title: Machine generated contents note: 1.Introduction; title: 1.1.Randomized Clinical Trials; title: 1.2.Observational Studies; title: 1.3.The Problem of Multiple Comparisons; title: 1.4.The Evolution of Available Data Streams; title: 1.5.The Hierarchy of Scientific Evidence; title: 1.6.Statistical Significance; title: 1.7.Summary; title: 2.Basic Statistical Concepts; title: 2.1.Introduction; title: 2.2.Relative Risk; title: 2.3.Odds Ratio; title: 2.4.Statistical Power; title: 2.5.Maximum Likelihood Estimation; title: 2.5.1.Example with a Closed Form Solution; title: 2.5.2.Example without a Closed Form Solution; title: 2.5.3.Bayesian Statistics; title: 2.5.4.Example; title: 2.6.Non-linear Regression Models; title: 2.7.Causal Inference; title: 2.7.1.Counterfactuals; title: 2.7.2.Average Treatment Effect; title: 3.Multi-level Models; title: 3.1.Introduction; title: 3.2.Issues Inherent in Longitudinal Data; title: 3.2.1.Heterogeneity; title: 3.2.2.Missing Data; title: 3.2.3.Irregularly Spaced Measurement Occasions; title: 3.3.Historical Background; title: Note continued: 3.4.Statistical Models for the Analysis of Longitudinal and/or Clustered Data; title: 3.4.1.Mixed-effects Regression Models; title: 3.4.1.1.Random Intercept Model; title: 3.4.1.2.Random Intercept and Trend Model; title: 3.4.2.Matrix Formulation; title: 3.4.3.Generalized Estimating Equation Models; title: 3.4.4.Models for Categorical Outcomes; title: 4.Causal Inference; title: 4.1.Introduction; title: 4.2.Propensity Score Matching; title: 4.2.1.Illustration; title: 4.2.2.Discussion; title: 4.3.Marginal Structural Models; title: 4.3.1.Illustration; title: 4.3.2.Discussion; title: 4.4.Instrumental Variables; title: 4.4.1.Illustration; title: 4.5.Differential Effects; title: 5.Analysis of Spontaneous Reports; title: 5.1.Introduction; title: 5.2.Proportional Reporting Ratio; title: 5.2.1.Discussion; title: 5.3.Bayesian Confidence Propagation Neural Network (BCPNN); title: 5.4.Empirical Bayes Screening; title: 5.5.Multi-item Gamma Poisson Shrinker; title: 5.6.Bayesian Lasso Logistic Regression; title: 5.7.Random-effect Poisson Regression; title: 5.7.1.Rate Multiplier; title: 5.8.Discussion; title: Note continued: 6.Meta-analysis; title: 6.1.Introduction; title: 6.2.Fixed-effect Meta-analysis; title: 6.2.1.Correlation Coefficient; title: 6.2.2.Mean Difference; title: 6.2.3.Relative Risk; title: 6.2.3.1.Inverse Variance Method; title: 6.2.3.2.Mantel-Haenszel Method; title: 6.2.4.Odds Ratio; title: 6.2.4.1.Inverse Variance Method; title: 6.2.4.2.Mantel-Haenszel Method; title: 6.2.4.3.Peto Method; title: 6.3.Random-effect Meta-analysis; title: 6.3.1.Sidik-Jonkman Estimator of Heterogeneity; title: 6.3.2.DerSimonian-Kacker Estimator of Heterogeneity; title: 6.3.3.REML Estimator of Heterogeneity; title: 6.3.4.Improved PM Estimator of Heterogeneity; title: 6.3.5.Example; title: 6.3.6.Issues with the Weighted Average in Meta-analysis; title: 6.4.Maximum Marginal Likelihood/Empirical Bayes Method; title: 6.4.1.Example: Percutaneous Coronary Intervention Based Strategy versus Medical Treatment Strategy; title: 6.5.Bayesian Meta-analysis; title: 6.5.1.WinBugs Example; title: 6.6.Confidence Distribution Framework for Meta-analysis; title: 6.6.1.The Framework; title: 6.6.1.1.Fixed-effects Model; title: Note continued: 6.6.1.2.Random-effects Model; title: 6.6.2.Meta-analysis of Rare Events under the CD Framework; title: 6.7.Discussion; title: 7.Ecological Methods; title: 7.1.Introduction; title: 7.2.Time Series Methods; title: 7.2.1.Generalized Event Count Model; title: 7.2.2.Tests of Serial Correlation; title: 7.2.3.Parameter-driven Generalized Linear Model; title: 7.2.4.Autoregressive Model; title: 7.3.State Space Model; title: 7.4.Change-point Analysis; title: 7.4.1.The u-chart; title: 7.4.2.Estimation of a Change-point; title: 7.4.3.Change-point Estimator for the INAR(1) Model; title: 7.4.3.1.Change-point Estimator for the Rate Parameter; title: 7.4.3.2.Change-point Estimator for the Dependence Parameter; title: 7.4.4.Change-point of a Poisson Rate Parameter with Linear Trend Disturbance; title: 7.4.5.Change-point of a Poisson Rate Parameter with Level and Linear Trend Disturbance; title: 7.4.6.Discussion; title: 7.5.Mixed-effects Poisson Regression Model; title: 8.Discrete-time Survival Models; title: 8.1.Introduction; title: 8.2.Discrete-time Ordinal Regression Model; title: Note continued: 8.3.Discrete-time Ordinal Regression Frailty Model; title: 8.4.Illustration; title: 8.5.Competing Risk Models; title: 8.5.1.Multinomial Regression Model; title: 8.5.2.Mixed-Effects Multinomial Regression Model; title: 8.6.Illustration; title: 8.6.1.Model Parameterization; title: 8.6.2.Results; title: 8.6.3.Discussion; title: 9.Research Synthesis; title: 9.1.Introduction; title: 9.2.Three-level Mixed-effects Regression Models; title: 9.2.1.Three-level Linear Mixed Model; title: 9.2.1.1.Illustration: Efficacy of Antidepressants; title: 9.2.2.Three-level Non-linear Mixed Model; title: 9.2.3.Three-level Logistic Regression Model for Dichotomous Outcomes; title: 9.2.3.1.Illustration: Safety of Antidepressants; title: 10.Analysis of Medical Claims Data; title: 10.1.Introduction; title: 10.2.Administrative Claims; title: 10.3.Observational Data; title: 10.4.Experimental Strategies; title: 10.4.1.Case-control Studies; title: 10.4.2.Cohort Studies; title: 10.4.3.Within-subject Designs; title: 10.4.3.1.Self-controlled Case Series; title: 10.4.4.Between-subject Designs; title: Note continued: 10.5.Statistical Strategies; title: 10.5.1.Fixed-effects Logistic and Poisson Regression; title: 10.5.2.Mixed-effects Logistic and Poisson Regression; title: 10.5.3.Sequential Testing; title: 10.5.4.Discrete-time Survival Models; title: 10.5.5.Stratified Cox Model; title: 10.5.6.Between and Within Models; title: 10.5.7.Fixed-effect versus Random-effect Models; title: 10.6.Illustrations; title: 10.6.1.Antiepileptic Drugs and Suicide; title: 10.6.2.Description of the Data, Cohort, and Key Design and Outcome Variables; title: 10.6.3.Statistical Methods; title: 10.6.4.Between-subject Analyses; title: 10.6.5.Within-subject Analysis; title: 10.6.6.Discrete-time Analysis; title: 10.6.7.Propensity Score Matching; title: 10.6.8.Self-controlled Case Series and Poisson Hybrid Models; title: 10.6.9.Marginal Structural Models; title: 10.6.10.Stratified Cox and Random-effect Survival Models; title: 10.6.11.Conclusion; title: 10.7.Conclusion; title: 11.Methods to be Avoided; title: 11.1.Introduction; title: 11.2.Spontaneous Reports; title: 11.3.Vote Counting; title: Note continued: 11.4.Simple Pooling of Studies; title: 11.5.Including Randomized and Non-randomized Trials in Meta-analysis; title: 11.6.Multiple Comparisons and Biased Reporting of Results; title: 11.7.Immortality Time Bias; title: 12.Summary and Conclusions; title: 12.1.Final Thoughts.