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Statistics for the Health Sciences
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Statistics for the Health Sciences
A Non-Mathematical Introduction



March 2012 | 584 pages | SAGE Publications Ltd

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.

 
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

This book by Dancey, Reidy and Rowe gives everything it promises: a non-mathematical introduction to statistics. It contains no mathematical formula, and gives a very basic explanation of statistical theory and the most common statistical analysis techniques. In my opnion too basic perhaps, because sometimes a simple formula can explain more than a page of text. The book provides clear instructions about perfoming the analyses with SPSS, using a lot of self-explanatory screenshots.

Mr Martijn Bours
Department of Epidemiology, Maastricht University
December 9, 2012

This book is excellent and provides clear and informative feedback, that makes a difficult subject simple

Dr Gemma Milligan
Dept of Sport & Exercise Science, Portsmouth University
November 6, 2012

I like the non-mathematical approach of this book, and I think it will be accessible to students struggling with the subject. Because it is targeted at health sciences, it covers techniques that might not otherwise be covered in a beginners' book, i.e. logistic regression and survival analysis, which is very welcome for me as a lecturer on a public health course.

Dr Penny Cook
College of Health & Social Care, Salford University
September 27, 2012

This textbook is an excellent non-mathematical introduction to statistics, although some ability in mathematics is required to be able to grasp many of the core concepts. I would recommend this text rather than making it essential reading for my students because the majority choose to undertake qualitative rather than quantitative research projects. It would be a highly useful resource for anyone planning to undertake statistical analysis using SPSS as there are a number of practical examples and exercises throughout the book. I have actually referred to it in conducting my own analyses and found it to be easy to follow.

Dr Shelina Visram
Sch of Health,Community & Educ Studies, Northumbria University
September 7, 2012

This book is going to be of great use to the half dozen or so quantitative empirical researchers that we see on this course and simply because of the number I will refer to this as supplemental. I can see the students really engaging with the simple page layouts and wording.

Mrs Paula Dring
Department of Occupational Therapy, Coventry University
September 7, 2012

I found this very easy to read and understand key concepts in basic statistics. It influenced the way I delivered sessions to students and I will recommend it to support learning with the next cohort of students that I do the same statistics sessions with.

Mr Steve Evans
School of Allied Health Professions, University of the West of England, Bristol
September 6, 2012

I would have adopted this book but I did not receive it in time and was not able to review it. Also, it did not have all the extra information (databases, powerpoints, etc) that came with the Andy Field book. However, I may use this book in the future.

Dr Vanessa Schick
Health Phys Ed Rec Dept, Indiana University - Bloomington
August 15, 2012

Highly recommended. User friendly and meaningful application

Miss Tracey Barnfather
Midwifery Division, Northampton University
July 28, 2012

Text provides a clear presentation of statistics which will provide undergraduate nursing students with a good resource for use in proposal development and / or sytematic reviews.

John Clarke
School of Nursing and Midwifery, Robert Gordon University
July 20, 2012

This is a great book for pharmacy students (and other health professionals) to gain an understanding of statistics and supplements the course currently provided to students well.

Dr Julie Prescott
Phamracy and biomendical sciences, UCLan
July 20, 2012

Sample Materials & Chapters

Chapter 1