Fundamentals of Biostatistics

Bernard Rosner (Autor)

Buch | Hardcover

888 Seiten

2015 | 8th edition
Brooks/Cole (Verlag)
978-1-305-26892-0 (ISBN)

Artikel merken

FUNDAMENTALS OF BIOSTATISTICS leads you through the methods, techniques, and computations of statistics necessary for success in the medical field. Every new concept is developed systematically through completely worked out examples from current medical research problems.

Bernard Rosner is a professor in the Department of Medicine, Harvard Medical School, and the Department of Biostatistics at the Harvard School of Public Health. Dr. Rosner's research activities currently include longitudinal data analysis, analysis of clustered continuous, binary and ordinal data, methods for the adjustment of regression models for measurement error and modeling of cancer incidence data.

Table of Contents.
Preface.
1. General Overview.
2. Descriptive Statistics.
Introduction.
Measures of Location.
Some Properties of the Arithmetic Mean.
Measures of Spread.
Some Properties of the Variance and Standard Deviation.
The Coefficient of Variation.
Grouped Data.
Graphic Methods.
Case Study 1: Effects of Lead Exposure on Neurological and Psychological Function in Children.
Case Study 2: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women.
Obtaining Descriptive Statistics on the Computer.
Summary.
Problems.
3. Probability.
Introduction.
Definition of Probability.
Some Useful Probabilistic Notation.
The Multiplication Law of Probability.
The Addition Law of Probability.
Conditional Probability.
Bayes’ Rule and Screening Tests.
Bayesian Inference.
ROC Curves.
Prevalence and Incidence.
Summary.
Problems.
4. Discrete Probability Distributions.
Introduction.
Random Variables.
The Probability-Mass Function for a Discrete Random Variable.
The Expected Value of a Discrete Random Variable.
The Variance of a Discrete Random Variable.
The Cumulative-Distribution Function of a Discrete Random Variable.
Permutations and Combinations.
The Binomial Distribution.
Expected Value and Variance of the Binomial Distribution.
The Poisson Distribution.
Computation of Poisson Probabilities.
Expected Value and Variance of the Poisson Distribution.
Poisson Approximation to the Binomial Distribution.
Summary.
Problems.
5. Continuous Probability Distributions.
Introduction.
General Concepts.
The Normal Distribution.
Properties of the Standard Normal Distribution.
Conversion from an N(µ, s2) Distribution to an N(0,1) Distribution.
Linear Combinations of Random Variables.
Normal Approximation to the Binomial Distribution.
Normal Approximation to the Poisson Distribution.
Summary.
Problems.
6. Estimation.
Introduction.
The Relationship Between Population and Sample.
Random-Number Tables.
Randomized Clinical Trials.
Estimation of the Mean of a Distribution.
Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women.
Estimation of the Variance of a Distribution.
Estimation for the Binomial Distribution.
Estimation for the Poisson Distribution.
One-Sided Cis.
The Bootstrap.
Summary.
Problems .
7. Hypothesis Testing: One-Sample Inference.
Introduction.
General Concepts.
One-Sample Test for the Mean of a Normal Distribution: One-Sided Alternatives.
One-Sample Test for the Mean of a Normal Distribution: Two-Sided Alternatives.
The Relationship Between Hypothesis Testing and Confidence Intervals.
The Power of a Test.
Sample-Size Determination.
One-Sample ?2 Test for the Variance of a Normal Distribution.
One-Sample Inference for the Binomial Distribution.
One-Sample Inference for the Poisson Distribution.
Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women.
Derivation of Selected Formulas.
Summary.
Problems.
8. Hypothesis Testing: Two-Sample Inference.
Introduction.
The Paired t Test.
Interval Estimation for the Comparison of Means from Two Paired Samples.
Two-Sample t Test for Independent Samples with Equal Variances.
Interval Estimation for the Comparison of Means from Two Independent Samples (Equal Variance Case).
Testing for the Equality of Two Variances.
Two-Sample t Test for Independent Samples with Unequal Variances.
Case Study: Effects of Lead Exposure on Neurologic and Psychological Function in Children.
Estimation of Sample Size and Power for Comparing Two Means.
The Treatment of Outliers.
Derivation of Equation 8.13.
Summary.
Problems.
9. Nonparametric Methods.
Introduction.
The Sign Test.
The Wilcoxon Signed-Rank Test.
The Wilcoxon Rank-Sum Test.
Case Study: Effects of Lead Exposure on Neurologic and Psychological Function in Children.
Permutation Tests.
Summary.
Problems.
10. Hypothesis Testing: Categorical Data.
Introduction.
Two-Sample Test for Binomial Proportions.
Fisher’s Exact Test.
Two-Sample Test for Binomial Proportions for Matched-Pair Data (McNemar’s Test).
Estimatio

Verlagsort	CA
Sprache	englisch
Maße	211 x 39 mm
Gewicht	1905 g
Themenwelt	Mathematik / Informatik ► Informatik
	Mathematik / Informatik ► Mathematik
	Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie
	Studium ► Querschnittsbereiche ► Epidemiologie / Med. Biometrie
	Naturwissenschaften ► Biologie ► Biochemie
	Technik ► Medizintechnik
	Wirtschaft ► Betriebswirtschaft / Management ► Rechnungswesen / Bilanzen
ISBN-10	1-305-26892-X / 130526892X
ISBN-13	978-1-305-26892-0 / 9781305268920
Zustand	Neuware