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

**by**Christine Dancey

1st

### 9781849203364

1849203369

Paperback

4/4/2012

SAGE Publications Ltd

## Summary

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

## Table of Contents

An Introduction to the Research Process | |

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 | |

Computer-Assisted Analysis | |

Overview of the Three Statistical Packages | |

Introduction to SPSS | |

Setting out Your Variable for within - and between - Group Designs. | |

Introduction to R | |

Introduction to SAS | |

Summary | |

Descriptive Statistics | |

Descriptive Statistics | |

Numerical Descriptive Statistics | |

Choosing a Measure of Central Tendency | |

Measures of Variation or Dispersion | |

Deviations from the Mean | |

Numerical Descriptives in SPSS | |

Frequencies | |

Graphical Statistics | |

Bar Charts | |

Line Graphs | |

Incorporating Variability into Graphs | |

Generating Graphs with Standard Deviations in SPSS | |

Graphs Showing Dispersion - Frequency Histogram | |

Box-Plots | |

Multiple Choice Questions | |

The Basis of Statistical Testing | |

Overview | |

Introduction | |

Samples and Populations | |

Distributions | |

Statistical Significance | |

Criticisms of NHST | |

Summary | |

MCQs | |

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 | |

Introduction to Data Screening and Cleaning | |

Overview | |

Introduction | |

Minimising Problems at the Design Stage | |

Entering Data into Databases/Statistical Packages | |

Accuracy | |

Using Descriptive Statistics to Help Identify Errors | |

Missing Data | |

Spotting Missing Data | |

Normality | |

Reporting Data Screening and Cleaning Procedures | |

Summary | |

Multiple Choice Questions | |

Differences Between Two Groups | |

Overview | |

Introduction | |

Conceptual Description of the T-Tests | |

Generalising to the Population | |

Cohen's d | |

Paired-T Test in SPSS | |

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 | |

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 | |

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 | |

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 | |

Partial Correlations | |

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 | |

Linear Regression | |

Overview | |

Introduction | |

Linear Regression 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 | |

Summary | |

Multiple Choice Questions | |

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 | |

Logistic Regression | |

Overview | |

Introduction | |

The Conceptual Basis of Logistic Regression | |

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 | |

MCQs | |

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 | |

Summary | |

Multiple Choice Questions | |

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