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Topics in Biostatistics Walter T. Ambrosius

Topics in Biostatistics By Walter T. Ambrosius

Topics in Biostatistics by Walter T. Ambrosius

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Summary

This book presents a multidisciplinary survey of biostatics methods, each illustrated with hands-on examples. It introduces advanced methods in statistics, including how to choose and work with statistical packages.

Topics in Biostatistics Summary

Topics in Biostatistics by Walter T. Ambrosius

This book presents a multidisciplinary survey of biostatics methods, each illustrated with hands-on examples. It introduces advanced methods in statistics, including how to choose and work with statistical packages. Specific topics of interest include microarray analysis, missing data techniques, power and sample size, statistical methods in genetics. The book is an essential resource for researchers at every level of their career.

Topics in Biostatistics Reviews

From the reviews:

It is useful to biologists as well as statisticians. The book describes the use of appropriate statistical methods and offers guidelines on selecting an appropriate test. ... The main strength of the book is the clear exposition of statistical tests. ... As biostatisticians we strongly recommend this book for libraries where research on molecular biology is going on, and students ... in biostatistics. ... helpful in understanding the essence of the statistical techniques to a wide range of researchers and students in biology and medicine. (Mukesh Srivastava and M. Abbas, Journal of Applied Statistics, Vol. 36 (4), April, 2009)

Table of Contents

Outline: 1. Study Design-The Basics Hyun Ja Lim and Raymond Hoffmann, Medical College of Wisconsin 1. Introduction 2. Experimental Studies 2.1 Randomized controlled studies 2.2 Historically controlled studies 2.3 Crossover studies 2.4 Factorial designs 2.5 Cluster or group allocation designs 3. Randomization 3.1 Complete or simple randomization 3.2 Block randomization 3.3 Stratified randomization 4. Blinding/Masking 5. Biases 6. Analyses 6.1 Compliance 6.2 Intention-to-treat (ITT) analysis 6.3 As received and per-protocol (PP) analysis 6.4 Subgroup analysis 6.5 Exploratory analyses 7. Study Interpretation 2. Observational Study Design Raymond Hoffmann and Hyun Ja Lim, Medical College of Wisconsin 1. Introduction 2. Cohort Studies 3. Prospective Cohort Studies and Retrospective Cohort Studies 4. Case-Control Studies 4.1 Odds Ratios 4.2 Choice of Controls 4.2 Case-Control Genetic Association Studies 4.3 Matching and Case-Control Studies 4.4 Biases in Case-Control Studies 4.5 Cross-Sectional Studies 5. Outcomes 6. More on Odds Ratios and Relative Risks 6.1 Relative Risks 6.2 Odds Ratios 7. Summary 3. Descriptive Statistics Todd Nick, Cincinnati Children's Hospital 1. Types of Data 2. Measures of location and spread 3. Normal distribution 4. Distribution of a mean 5. Distribution of a variance (including degrees of freedom) 6. Distribution of a proportion 4. Basic Principles of Statistical Inference Wanzhu Tu, Indiana University School of Medicine 1. Introduction 2. Parameter Estimation 2.1 Point Estimation 2.2 Confidence Interval Estimation 2.2.1 Large Sample Confidence Interval for the Mean 2.2.2 Student t-distribution 2.2.3 Small Sample Confidence Interval for the Mean 2.2.4 Simultaneous Inference: Bonferroni's Multiplicity Adjustment 2.2.5 Confidence Interval for the Variance 2.2.6 One-Sided Confidence Intervals 3. Hypothesis Testing 3.1 Understanding Hypothesis Testing 3.2 One sample t test 3.3 An alternaive Decision Rule: P-value 3.4 Errors, Power, and Sample Size 3.5 Statistical Significance and Practical Significance 5. Statistical Inference on Categorical Variables Susan Perkins, Indiana University School of Medicine 1. Introduction 1.1 What is Categorical Data? 1.2 Categorical Data Distributions 1.3 General Notation 1.4 Statistical Analysis Using Categorical Data 2. The Binomial Distribution and the Normal Approximation to the Binomial Distribution 2.1 The Binomial Experiment 2.2 The Binomial Distribution 2.3 The Normal Approximation to the Binomial 3. Estimation and Testing of Single Proportions/Two Proportions 3.1 Estimation of a Single Proportion or the Difference Between Two Proportions 3.2 Hypothesis Testing with a Single Proportion or the Difference Between Two Proportions 3.3 Assumptions 4. Tests of Association 4.1 2x2 Tables 4.2 RxC Tables 4.3 Relationship Between Tests of Independence and Homogeneity 4.4 Fisher's Exact Test 5. McNemar's Test 6. Sample Size Estimation 7. Discussion 6. Development and Evaluation of Classifiers Todd A. Alonzo, University of Southern California, and Margaret Sullivan Pepe, Fred Hutchinson Cancer Research Center and University of Washington 1. Introduction 2. Measures of Classification Accuracy 2.1 True and False Positive Fractions 2.2 Predictive Values 2.3 Diagnostic Likelihood Ratios 2.4 ROC Curves 2.5 Selecting a Measure of Accuracy 3. Basics of Study Design 3.1 Case-control versus Cohort Designs 3.2 Paired versus Unpaired Designs 3.3 Blinding 3.4 Avoiding Bias 3.5 Factors Affecting Test Performance 4. Estimating Performance from Data 4.1 Single binary test 4.2 Comparison of TPF and FPF for two binary tests 4.2.1 Unpaired

Additional information

NLS9781617376238
9781617376238
161737623X
Topics in Biostatistics by Walter T. Ambrosius
Walter T. Ambrosius
Methods in Molecular Biology
New
Paperback
Humana Press Inc.
2010-11-19
528
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
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