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



April 2012 | 584 pages | SAGE Publications Ltd
This is a highly accessible textbook on understanding statistics for the health sciences, both conceptually and via SPSS. The authors give clear explanations of the concepts underlying statistical analyzes and descriptions of how these analyzes are applied in health sciences research without complex statistical formulae. The book takes students from the basics of research design, hypothesis testing, and descriptive statistical techniques through to more advanced inferential statistical tests that health sciences students are likely to encounter. Exercises and tips throughout the book allow students to practice using SPSS. 


 
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

Useful text for students struggling with determining the appropriateness of statistical methods when reviewing studies

Mrs Judith Carrier
School of Nursing & Midwifery Studies, Cardiff University
June 21, 2012

Excellent as a supplemental text for behavioral sciences but due to the need for sociological examples not 100 % suitable as an essential book for sociologists.

Dr Gerhard Majce
Department of Sociology, University of Vienna
June 18, 2012

Not a book to "dip in and out of" for a bit of light reading. However, could be a valuable resource when undertaking reaserch modules / research apsects of health care science courses which require further definitions or understanding of aspects of research or research designs. There are questions and completed answer sessions at the end of chapters highlighting dersired outcomes which are very useful.

Mr Brian Shilton
Community Health , Glamorgan University
June 18, 2012

This is a fantastic book for readers who have little background in Mathematicss to undertsand the use of statistics in Research. A very good read for all, especially beginners.

Dr Jennifer Loke
Department of Nursing & Midwifery, Hull University
June 18, 2012

Excellent introduction to statistical methods and integrating SPSS for students from a non-quantitative background. Should have a wider audience in the non-health fields such as social and media students studying quants.

Mr Hugh Maguiness
School of Social Sciences, University of the West of Scotland
June 15, 2012

A useful text providing an accessible view of statistical data and interpretation within research methods.

Mrs Liz Cade
Health , Glyndwr University
June 7, 2012

clearly written and informative text that helps students to understand the process of statistical analysis and more importantly guides students through applying such analysis to data they generate as part of their studies.

Mr Keith Bradley-Adams
Nursing (St David's Campus), Swansea University
June 6, 2012

Brilliant book, written in an easy to understand manner. I wish i had read this years ago!!!

Mrs Nicola Credland
Department of Nursing & Midwifery, Hull University
May 30, 2012

This book clearly outlines statistical information making it accessible for students and practitioners. Each section uses an overview and introduction to outline what is to come and a summary and MCQ to consolidate information. A very useful book to assist in understanding something that many consider quite daunting.

Ms Sarah Maris-Shaw
Allied Health Sceinces, London South Bank University
May 21, 2012

Excellent informative text book

Miss Deborah Heron
Faculty of Medicine, Health & Life Sci, Southampton University
May 18, 2012

Sample Materials & Chapters

Chapter 1