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