Evaluating Drug Literature: A Statistical Approach / Edition 1

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Overview

Important new textbook gives students of pharmacy a one-stop resource to develop the necessary skills to find, read, understand, and evaluate drug literature. Epidemiological and mathematical concepts are explained clearly and concisely with real examples, not hypothetical case studies. Key concepts correlation and regression analysis, survival curve analysis, medical informatics, research process and experimental design are presented clearly and made relevant to the pharmacy arena.
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Editorial Reviews

Doody's Review Service
Reviewer: Amy E. Lodolce, PharmD, BCPS (University of Illinois at Chicago College of Pharmacy)
Description: This book provides the reader with information on retrieving and interpreting drug information while focusing on applying these concepts to evaluating the biomedical literature.
Purpose: The purpose is to assist pharmacists in retrieving and evaluating drug information in order to respond to requests from patients and other healthcare providers.
Audience: The target audience is practicing pharmacists and pharmacy students. Pharmacy educators may also find this book useful when teaching literature evaluation and statistical concepts. Prior exposure to statistical concepts is beneficial before using this text.
Features: The book covers searching and evaluating drug literature, clinical trial design, and descriptive and inferential statistics. Statistics accounts for the largest portion of the book and hypothesis testing, confidence intervals, parametric/nonparametric tests, and correlation along with other topics are covered. Although the book does not contain as detailed information as statistics textbooks, it has several examples to emphasize concepts and aid in application. These examples are from published studies and should be especially beneficial when learning to evaluate statistical material in the biomedical literature. Each chapter concludes with study questions and has a reference list that can be used to identify further sources of information. Figures and tables are used throughout the book to visually demonstrate concepts. A glossary and several useful appendixes contain commonly used statistical tables such as t-distribution and a list of healthcare-related web sites.
Assessment: This is a resource for practicing pharmacists who want to enhance their drug information skills in order to communicate with patients and the healthcare community. It can also serve as an additional resource for pharmacy students and pharmacy educators to supplement information in standard drug information and statistics textbooks.

3 Stars from Doody
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Product Details

  • ISBN-13: 9780071347297
  • Publisher: McGraw-Hill Companies, The
  • Publication date: 5/8/2001
  • Edition number: 1
  • Pages: 369
  • Product dimensions: 6.38 (w) x 9.32 (h) x 1.25 (d)

Table of Contents

Chapter 1: Introduction to Drug Literature.Chapter 2: Searching Drug Literature. Chapter 3: The Publication Process. Chapter 4: Classification of Study Design: Observational Research. Chapter 5: Study Design: Experimental Research. Chapter 6: Data Measurement, Description, and Presentation. Chapter 7: Concepts in Inferential Statistics: Distributions, Confidence Intervals, and Hypothesis Testing. Chapter 8: Evaluating Statistical Results: Parametric Tests. Chapter 9: Evaluating Statistical Results: Nonparametric Tests. Chapter 10: Evaluating Statistical Results: Correlation, Regression, Survival Life Analysis. Chapter 11: Critical Appraisal of Meta-Analysis. Chapter 12: Evaluating Pharmacoeconomic Literature. Chapter 13: Managing Uncertainty in Decision Analysis with Sensitivity Analysis. Chapter 14: Ethical Concerns in Drug Research and Literature Evaluation. Chapter 15: The Future of Drug Information and the Internet. Answer Key. (and more...)
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Sort by: Showing 1 Customer Reviews
  • Anonymous

    Posted June 18, 2003

    Great for pharmacy students

    This book is a great resource for students who need statistics written in 'layman' terms. The definitions and examples are easy to understand. I highly recommend this book.

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