Introductory Applied Biostatistics

ISBN-10: 053442399X
ISBN-13: 9780534423995
Edition: 2006
List price: $234.95 Buy it from $27.60 Rent it from $14.74
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Description: INTRODUCTORY APPLIED BIOSTATISTICS provides a solid and engaging background for students learning to apply and appropriately interpret statistical applications in the medical and public health fields. The many examples drawn directly from the  More...

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Book details

List price: $234.95
Copyright year: 2006
Publisher: Brooks/Cole
Publication date: 3/16/2005
Binding: Hardcover
Pages: 672
Size: 7.50" wide x 9.20" long x 1.20" tall
Weight: 3.344
Language: English

INTRODUCTORY APPLIED BIOSTATISTICS provides a solid and engaging background for students learning to apply and appropriately interpret statistical applications in the medical and public health fields. The many examples drawn directly from the authors' remarkable clinical experiences with applied biostatistics make this text relevant, practical, and interesting for students. This flexible textbook encourages students to master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. The majority of the textbook addresses methods for statistical inference, including one- and two-sample tests for means and proportions, analysis of variance techniques, correlation, and regression analysis. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results.

Alexa Beiser is Professor of Biostatistics in the School of Public Health at Boston University. She received her M.A. from University of California at San Diego, and her Ph.D. from Boston University. Her research interests include clinical trials methodology, statistical computing, and survival analysis. Dr. Beiser joined the Framingham Study in 1994 after spending many years collaborating on a variety of pediatric research projects. She is primarily involved in the investigation of risk factors for stroke, dementia, and Alzheimer's Disease using data collected as part of the Framingham Study. Dr. Beiser's foremost methodological interest is in estimation of lifetime risk of disease. Dr. Beiser has published articles in the NEW ENGLAND JOURNAL OF MEDICINE, the JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, STATISTICS IN MEDICINE, STROKE and NEUROLOGY. She enjoys reading, traveling and spending time with her four children.

Introduction
Motivation
Introduction
Vocabulary
Population Parameters
Sampling and Sample Statistics
Statistical Inference
Summarizing Data
Introduction
Background
Descriptive Statistics and Graphical Methods
Key Formulas
Statistical Computing
Problems
Probability
Introduction
Background
First Principles
Combinations and Permutations
The Binomial Distribution
The Normal Distribution
Key Formulas
Applications Using SAS
Problems
Sampling Distributions
Introduction
Background
The Central Limit Theorem
Key Formulas
Applications Using SAS
Problems
Statistical Inference: Procedures For �
Introduction
Estimating �
Testing Hypotheses Concerning �
Key Formulas
Statistical Computing
Problems
Statistical inference: procedures for (�1-�2) introduction
Statistical Inference Concerning (�1-�2)
Power and Samples Size Determination
Key Formulas
Statistical Computing
Problems
Categorical Data
Introduction
Statistical Inference Concerning p
Cross-tabulation Tables
Diagnostic Tests: Sensitivity and Specificity
Statistical Inference Concerning (p1-p2)
Chi-Square Tests
Precision, Power and Sample Size Determination
Key Formulas
Statistical Computing
Problems
Comparing Risks In Two Populations
Introduction
Effect Measures
Confidence Intervals for Effect Measures
The Chi-Square Test of Homogeneity
Fisher's Exact Test
Cox-Mantel-Haenzel Method
Precision, Power and Sample Size Determination
Key Formulas
Statistical Computing
Problems
Analysis Of Variance
Introduction
Background Logic
Notation and Examples
Fixed vs
Random Effects Models
Evaluating Treatment Effects
Multiple Comparisons
Repeated Measures Analysis of Variance
Key Formulas
Statistical Computing
Problems
Correlation And Regression
Introduction
Correlation Analysis
Simple Linear Regression
Multiple Regression Analysis
Logistic Regression Analysis
Key Formulas
Statistical Computing
Problems
Logistic Regression Analysis
Introduction
The Logistic Model
Statistical Inference for Simple Logistic Regression
Multiple Logistic Regression
ROC Area
Key Formulas
Statistical Computing
Problems
Nonparametric Tests
Introduction
The Sign Test (Two Dependent Samples Test)
The Wilcoxon Signed-Rank Test (Two Dependent Samples)
The Wilcoxon Rank Sum Test (Two Independent Samples)
The Kruskal-Wallis Test (k Independent Samples)
Spearman Correlation (Correlation between Variables)
Key Formulas
Statistical Computing
Problems
Introduction To Survival Analysis
Introduction
Incomplete Follow-Up
Time to Event
Survival Analysis Techniques
Introduction to Statistical Computing Using SAS
Introduction to SAS
The Data Step
Statistical Tables
Statistical Tables
SAS Programs used to generate table entries

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