Christine Dancey, John Reidy, Richard Rowe

Statistics for the Health Sciences

A Non-Mathematical Introduction

• Broschiertes Buch

Produktbeschreibung

Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae.

The textbook takes students from the basics of research design, hypothesis testing and descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter. The strengths and weaknesses of different techniques are critically appraised throughout, and the authors emphasise how they may be used both in research and to inform best practice care in health settings.

Exercises and tips throughout the book allow students to practice using SPSS. The companion website provides further practical experience of conducting statistical analyses. Features include:

- multiple choice questions for both student and lecturer use

- full Powerpoint slides for lecturers

- practical exercises using SPSS

- additional practical exercises using SAS and R

This is an essential textbook for students studying beginner and intermediate level statistics across the health sciences.

Produktdetails

• Verlag: SAGE Publications Ltd / Sage Publications
• Artikelnr. des Verlages: B03357P
• Seitenzahl: 584
• Erscheinungstermin: 19. März 2012
• Englisch
• Abmessung: 235mm x 191mm x 37mm
• Gewicht: 1478g
• ISBN-13: 9781849203364
• ISBN-10: 1849203369
• Artikelnr.: 33677489

Inhaltsangabe

PART ONE: AN INTRODUCTION TO THE RESEARCH PROCESS
Overview
The Research Process
Concepts and Variables
Levels of Measurement
Hypothesis Testing
Evidence-Based Practice
Research Designs
Multiple-Choice Questions
PART TWO: COMPUTER-ASSISTED ANALYSIS
Overview
Overview of the Three Statistical Packages
Introduction to SPSS
Setting out Your Variables for within - and between-Group Designs
Introduction to R
Introduction to SAS
Summary
Exercises
PART THREE: DESCRIPTIVE STATISTICS
Overview
Anaylsing Data
Descriptive Statistics
Numerical Descriptive Statistics
Choosing a Measure of Central Tendency
Measures of Variation or Dispersion
Deviations from the Mean
Numerical Descriptives in SPSS
Graphical Statistics
Bar Charts
Line Graphs
Incorporating Variability into Graphs
Generating Graphs with Standard Deviations in SPSS
Graphs Showing Dispersion - Frequency Histogram
Box-Plots
Summary
SPSS Exercise
Multiple Choice Questions
PART FOUR: THE BASIS OF STATISTICAL TESTING
Overview
Introduction
Samples and Populations
Distributions
Statistical Significance
Criticisms of NHST
Generating Confidence Intervals in SPSS
Summary
SPSS Exercise
Multiple Choice Questions
PART FIVE: EPIDEMIOLOGY
Overview
Introduction
Estimating the Prevalence of Disease
Difficulties in Estimating Prevalence
Beyond Prevalence: Identifying Risk Factors for Disease
Risk Ratios
The Odds-Ratio
Establishing Causality
Case-Control Studies
Cohort Studies
Experimental Designs
Summary
Multiple Choice Questions
PART SIX: INTRODUCTION TO DATA SCREENING AND CLEANING
Overview
Introduction
Minimising Problems at the Design Stage
Entering Data into Databases/Statistical Packages
The Dirty Dataset
Accuracy
Using Descriptive Statistics to Help Identify Errors
Missing Data
Spotting Missing Data
Normality
Screening Groups Separately
Reporting Data Screning and Cleaning Procedures
Summary
Multiple Choice Questions
PART SEVEN: DIFFERENCES BETWEEN TWO GROUPS
Overview
Introduction
Conceptual Description of the t-Tests
Generalising to the Population
Independent Groups t-Test in SPSS
Cohen's d
Paired t-Test in SPSS
Two-Sample z-Test
Non-Parametric Tests
Mann-Whitney: for Independent Groups
Mann-Whitney Test in SPSS
Wilcoxon Signed Rank Test: For Repeated Measures
Wilcoxon Signed Rank Test in SPSS
Adjusting for Multiple Tests
Summary
Multiple Choice Questions
PART EIGHT: DIFFERENCES BETWEEN THREE OR MORE CONDITIONS
Overview
Introduction
Conceptual Description of the (Parametric) ANOVA
One-Way ANOVA
One-way ANOVA in SPSS
ANOVA Models for Repeated-Measures Designs
Repeated Measures ANOVA in SPSS
Non-parametric Equivalents
The Kruskal-Wallis Test
Kruskal-Wallis and the Median Test in SPSS
The Median Test
Friedman's ANOVA for Repeated Measures
Friedman's ANOVA in SPSS
Summary
Multiple Choice Questions
PART NINE: TESTING ASSOCIATIONS BETWEEN CATEGORICAL VARIABLES
Overview
Introduction
Rationale of Contingency Table Analysis
Running the Analysis in SPSS
Measuring Effect Size in Contingency Table Analysis
Larger Contingency Tables
Contingency Table Analysis Assumptions
The X2 Goodness of Fit Test
Running the X2 Goodness of Fit Test Using SPSS
Summary
Multiple Choice Questions
PART TEN: MEASURING AGREEMENT: CORRELATIONAL TECHNIQUES
Overview
Introduction
Bivariate Relationships
Perfect Correlations
Calculating the Correlation Pearson's R Using SPSS.
How to obtain Scatterplots
Variance Explanation of R
Obtaining Correlational Analysis in SPSS: Exercise
Partial Correlations
Shared and Unique Variance: Conceptual Understanding Relating to Partial Corrections
Spearman's Rho
Other uses for Correlational Techniques
Reliability of Measures
Internal Consistency
Inter Rater Reliability
Validity
Percentage Agreement
Cohen's Kappa
Summary
Multiple Choice Questions
PART 11: LINEAR REGRESSION
Overview
Introduction
Linear Regression in SPSS
Obtaining teh Scatterplot with Regression Line and Confidence Intervals in SPSS
Assumptions Underlying Linear Regression
Dealing with Outliers
What happens if the Correlation Between X and Y is Near Zero?
Using Regression to Predict Missing Data in SPSS
Prediction of Missing Scores on Cognitive Failures in SPSS
Summary
Multiple-Choice Questions
PART TWELVE: STANDARD MULTIPLE REGRESSION
Overview
Introduction
Multiple Regression in SPSS
Variables in the Equation
The Regression Equation
Predicting an Individual's Score
Hypothesis Testing
Other Types of Multiple Regression
Hierarchical Multiple Regression
Summary
Multiple Choice Questions
PART THIRTEEN: LOGISTIC REGRESSION
Overview
Introduction
The Conceptual Basis of Logistic Regression
Writing up the Result
Logistic Regression with Multiple Predictor Variables
Logistic Regression with Categorical Predictors
Categorical Predictors with Three or More Levels
Summary
Multiple Choice Questions
Interventions and Analysis of Change
Overview
Interventions
How do we Know Whether Interventions are Effective?
Randomised Control Trials (RCTs)
Designing an RCT: CONSORT
The CONSORT Flow Chart
Important Features of an RCT
Blinding
Analysis of RCTs
Running an ANCOVA in SPSS
McNemar's Test of Change
Running McNemar's Test in SPSS
The Sign Test
Running the Sign Test using SPSS
Intention to Treat Analysis
Crossover Designs
Single Case Designs (N= 1)
Generating Single Case Design Graphs Using SPSS
Summary
SPSS Exercise
Multiple Choice Questions
PART FIFTEEN: SURVIVAL ANALYSIS: AN INTRODUCTION
Overview
Introduction
Survival Curves
The Kaplan-Meier Survival Function
Kaplan-Meier Survival Analyses in SPSS
Comparing Two Survival Curves - the Mantel-Cox test
Mantel-Cox using SPSS
Hazard
Hazard Curves
Hazard Functions in SPSS
Writing up a Survival Analysis
Summary
SPSS Exercise
Multiple Choice Questions

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PART ONE: AN INTRODUCTION TO THE RESEARCH PROCESS Overview The Research Process Concepts and Variables Levels of Measurement Hypothesis Testing Evidence-Based Practice Research Designs Multiple-Choice Questions PART TWO: COMPUTER-ASSISTED ANALYSIS Overview Overview of the Three Statistical Packages Introduction to SPSS Setting out Your Variables for within - and between-Group Designs Introduction to R Introduction to SAS Summary Exercises PART THREE: DESCRIPTIVE STATISTICS Overview Anaylsing Data Descriptive Statistics Numerical Descriptive Statistics Choosing a Measure of Central Tendency Measures of Variation or Dispersion Deviations from the Mean Numerical Descriptives in SPSS Graphical Statistics Bar Charts Line Graphs Incorporating Variability into Graphs Generating Graphs with Standard Deviations in SPSS Graphs Showing Dispersion - Frequency Histogram Box-Plots Summary SPSS Exercise Multiple Choice Questions PART FOUR: THE BASIS OF STATISTICAL TESTING Overview Introduction Samples and Populations Distributions Statistical Significance Criticisms of NHST Generating Confidence Intervals in SPSS Summary SPSS Exercise Multiple Choice Questions PART FIVE: EPIDEMIOLOGY Overview Introduction Estimating the Prevalence of Disease Difficulties in Estimating Prevalence Beyond Prevalence: Identifying Risk Factors for Disease Risk Ratios The Odds-Ratio Establishing Causality Case-Control Studies Cohort Studies Experimental Designs Summary Multiple Choice Questions PART SIX: INTRODUCTION TO DATA SCREENING AND CLEANING Overview Introduction Minimising Problems at the Design Stage Entering Data into Databases/Statistical Packages The Dirty Dataset Accuracy Using Descriptive Statistics to Help Identify Errors Missing Data Spotting Missing Data Normality Screening Groups Separately Reporting Data Screning and Cleaning Procedures Summary Multiple Choice Questions PART SEVEN: DIFFERENCES BETWEEN TWO GROUPS Overview Introduction Conceptual Description of the t-Tests Generalising to the Population Independent Groups t-Test in SPSS Cohen
s d Paired t-Test in SPSS Two-Sample z-Test Non-Parametric Tests Mann-Whitney: for Independent Groups Mann-Whitney Test in SPSS Wilcoxon Signed Rank Test: For Repeated Measures Wilcoxon Signed Rank Test in SPSS Adjusting for Multiple Tests Summary Multiple Choice Questions PART EIGHT: DIFFERENCES BETWEEN THREE OR MORE CONDITIONS Overview Introduction Conceptual Description of the (Parametric) ANOVA One-Way ANOVA One-way ANOVA in SPSS ANOVA Models for Repeated-Measures Designs Repeated Measures ANOVA in SPSS Non-parametric Equivalents The Kruskal-Wallis Test Kruskal-Wallis and the Median Test in SPSS The Median Test Friedman
s ANOVA for Repeated Measures Friedman
s ANOVA in SPSS Summary Multiple Choice Questions PART NINE: TESTING ASSOCIATIONS BETWEEN CATEGORICAL VARIABLES Overview Introduction Rationale of Contingency Table Analysis Running the Analysis in SPSS Measuring Effect Size in Contingency Table Analysis Larger Contingency Tables Contingency Table Analysis Assumptions The X2 Goodness of Fit Test Running the X2 Goodness of Fit Test Using SPSS Summary Multiple Choice Questions PART TEN: MEASURING AGREEMENT: CORRELATIONAL TECHNIQUES Overview Introduction Bivariate Relationships Perfect Correlations Calculating the Correlation Pearson
s R Using SPSS. How to obtain Scatterplots Variance Explanation of R Obtaining Correlational Analysis in SPSS: Exercise Partial Correlations Shared and Unique Variance: Conceptual Understanding Relating to Partial Corrections Spearman
s Rho Other uses for Correlational Techniques Reliability of Measures Internal Consistency Inter Rater Reliability Validity Percentage Agreement Cohen
s Kappa Summary Multiple Choice Questions PART 11: LINEAR REGRESSION Overview Introduction Linear Regression in SPSS Obtaining teh Scatterplot with Regression Line and Confidence Intervals in SPSS Assumptions Underlying Linear Regression Dealing with Outliers What happens if the Correlation Between X and Y is Near Zero? Using Regression to Predict Missing Data in SPSS Prediction of Missing Scores on Cognitive Failures in SPSS Summary Multiple-Choice Questions PART TWELVE: STANDARD MULTIPLE REGRESSION Overview Introduction Multiple Regression in SPSS Variables in the Equation The Regression Equation Predicting an Individual
s Score Hypothesis Testing Other Types of Multiple Regression Hierarchical Multiple Regression Summary Multiple Choice Questions PART THIRTEEN: LOGISTIC REGRESSION Overview Introduction The Conceptual Basis of Logistic Regression Writing up the Result Logistic Regression with Multiple Predictor Variables Logistic Regression with Categorical Predictors Categorical Predictors with Three or More Levels Summary Multiple Choice Questions Interventions and Analysis of Change Overview Interventions How do we Know Whether Interventions are Effective? Randomised Control Trials (RCTs) Designing an RCT: CONSORT The CONSORT Flow Chart Important Features of an RCT Blinding Analysis of RCTs Running an ANCOVA in SPSS McNemar
s Test of Change Running McNemar
s Test in SPSS The Sign Test Running the Sign Test using SPSS Intention to Treat Analysis Crossover Designs Single Case Designs (N= 1) Generating Single Case Design Graphs Using SPSS Summary SPSS Exercise Multiple Choice Questions PART FIFTEEN: SURVIVAL ANALYSIS: AN INTRODUCTION Overview Introduction Survival Curves The Kaplan-Meier Survival Function Kaplan-Meier Survival Analyses in SPSS Comparing Two Survival Curves - the Mantel-Cox test Mantel-Cox using SPSS Hazard Hazard Curves Hazard Functions in SPSS Writing up a Survival Analysis Summary SPSS Exercise Multiple Choice Questions

Rezensionen

'Statistics for the Health Sciences engagingly presents the key analytic issues that students and professionals need to understand in the most accessible and vivid way possible. Full of real examples and practical exercises, the book successfully avoids getting bogged down with complex maths and formulae' - Dennis Howitt at Loughborough University The chapter overviews, absence of statistical formulae and use of appropriate examples and student exercises make this a very 'hands on' and practical text' - Merryl E Harvey, Birmingham City University