Statistics For The Health Sciences: A Non-Mathematical Introduction

Description

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. Title Page......Page 3 Copyright......Page 6 Contents......Page 8 About the Authors......Page 15 Preface......Page 16 Acknowledgements......Page 18 Companion Website......Page 19 1 An Introduction to the Research Process......Page 20 Overview......Page 21 The Research Process......Page 22 Concepts and Variables......Page 24 Levels of Measurement......Page 27 Evidence-Based Practice......Page 29 Research Designs......Page 30 Multiple Choice Questions......Page 35 2 Computer-Assisted Analysis......Page 38 Overview of the Three Statistical Packages......Page 39 Introduction to SPSS......Page 42 Setting out Your Variables for Within- and Between-Group Designs......Page 52 Introduction to R......Page 58 Introduction to SAS......Page 70 Exercises......Page 81 3 Descriptive Statistics......Page 84 Analysing Data......Page 85 Descriptive Statistics......Page 86 Numerical Descriptive Statistics......Page 87 Choosing a Measure of Central Tendency......Page 90 Measures of Variation or Dispersion......Page 91 Deviations from the Mean......Page 94 Numerical Descriptives in SPSS......Page 95 Bar Charts......Page 99 Line Graphs......Page 107 Incorporating Variability into Graphs......Page 109 Generating Graphs with Standard Deviations in SPSS......Page 110 Graphs Showing Dispersion – Frequency Histogram......Page 111 Box-Plots......Page 116 Summary......Page 120 Multiple Choice Questions......Page 121 4 The Basis of Statistical Testing......Page 125 Introduction......Page 126 Samples and Populations......Page 127 Distributions......Page 139 Statistical Significance......Page 149 Criticisms of NHST......Page 150 Generating Confidence Intervals in SPSS......Page 154 Multiple Choice Questions......Page 159 5 Epidemiology......Page 162 Introduction......Page 163 Difficulties in Estimating Prevalence......Page 164 Beyond Prevalence: Identifying Risk Factors for Disease......Page 166 Risk Ratios......Page 167 The Odds-Ratio......Page 168 Establishing Causality......Page 169 Case-Control Studies......Page 170 Cohort Studies......Page 172 Experimental Designs......Page 173 Multiple Choice Questions......Page 174 6 Introduction to Data Screening and Cleaning......Page 177 Introduction......Page 178 Minimising Problems at the Design Stage......Page 179 The Dirty Dataset......Page 180 Using Descriptive Statistics to Help Identify Errors......Page 181 Missing Data......Page 183 Spotting Missing Data......Page 187 Normality......Page 191 Screening Groups Separately......Page 193 Reporting Data Screening and Cleaning Procedures......Page 194 Multiple Choice Questions......Page 195 7 Differences Between Two Groups......Page 198 Introduction......Page 199 Conceptual Description of the t-Tests......Page 201 Generalising to the Population......Page 204 Independent Groups t-Test in SPSS......Page 205 Cohen’s d......Page 209 Paired t-Test in SPSS......Page 211 Two-Sample z-Test......Page 216 Mann–Whitney Test in SPSS......Page 217 Wilcoxon Signed Rank Test in SPSS......Page 223 Multiple Choice Questions......Page 226 8 Differences Between Three or More Conditions......Page 231 Introduction......Page 232 Conceptual Description of the (Parametric) ANOVA......Page 233 One-Way ANOVA......Page 234 One-way ANOVA in SPSS......Page 236 ANOVA Models for Repeated-Measures Designs......Page 241 Repeated-Measures ANOVA in SPSS......Page 242 The Kruskal–Wallis Test......Page 247 Kruskal–Wallis and the Median Test in SPSS......Page 248 The Median Test......Page 251 Friedman’s ANOVA for Repeated Measures......Page 252 Friedman’s ANOVA in SPSS......Page 253 Multiple Choice Questions......Page 256 9 Testing Associations Between Categorical Variables......Page 261 Introduction......Page 262 Rationale of Contingency Table Analysis......Page 264 Running the Analysis in SPSS......Page 265 Measuring Effect Size in Contingency Table Analysis......Page 270 Larger Contingency Tables......Page 271 Contingency Table Analysis Assumptions......Page 272 The χ2 Goodness-of-Fit Test......Page 274 Running the χ2 Goodness-of-Fit Test Using SPSS......Page 276 Multiple Choice Questions......Page 278 10 Measuring Agreement: Correlational Techniques......Page 282 Introduction......Page 283 Bivariate Relationships......Page 284 Perfect Correlations......Page 289 Calculating the Correlation Pearson’s r Using SPSS......Page 291 How to Obtain Scatterplots......Page 293 Variance Explanation of r......Page 297 Partial Correlations......Page 299 Shared and Unique Variance: Conceptual Understanding Relating to Partial Correlations......Page 301 Spearman’s rho......Page 303 Reliability of Measures......Page 305 Validity......Page 306 Summary......Page 307 Multiple Choice Questions......Page 308 11 Linear Regression......Page 312 Introduction......Page 313 Linear Regression in SPSS......Page 317 Obtaining the Scatterplot with Regression Line and Confidence Intervals in SPSS......Page 320 Dealing with Outliers......Page 326 What Happens if the Correlation between X and Y is Near Zero?......Page 329 Using Regression to Predict Missing Data in SPSS......Page 331 Prediction of Missing Scores on Cognitive Failures in SPSS......Page 333 Multiple Choice Questions......Page 335 12 Standard Multiple Regression......Page 339 Introduction......Page 340 Multiple Regression in SPSS......Page 341 Variables in the Equation......Page 343 Predicting an Individual’s Score......Page 346 Hypothesis Testing......Page 347 Other Types of Multiple Regression......Page 349 Hierarchical Multiple Regression......Page 351 Summary......Page 353 Multiple Choice Questions......Page 354 13 Logistic Regression......Page 358 Introduction......Page 359 The Conceptual Basis of Logistic Regression......Page 360 Writing up the Result......Page 367 Logistic Regression with Multiple Predictor Variables......Page 368 Logistic Regression with Categorical Predictors......Page 372 Categorical Predictors with Three or More Levels......Page 373 Multiple Choice Questions......Page 375 14 Interventions and Analysis of Change......Page 379 How Do We Know Whether Interventions Are Effective?......Page 380 Randomised Control Trials (RCTs)......Page 383 Designing an RCT: CONSORT......Page 384 The CONSORT Flow Chart......Page 386 Important Features of an RCT......Page 388 Blinding......Page 391 Analysis of RCTs......Page 392 Running an ANCOVA in SPSS......Page 393 McNemar’s Test of Change......Page 395 Running McNemar’s Test in SPSS......Page 396 The Sign Test......Page 398 Intention to Treat Analysis......Page 399 Crossover Designs......Page 401 Single-Case Designs (N = 1)......Page 402 Generating Single-Case Design Graphs Using SPSS......Page 407 Multiple Choice Questions......Page 411 15 Survival Analysis: An Introduction......Page 415 Introduction......Page 416 Survival Curves......Page 419 The Kaplan–Meier Survival Function......Page 423 Kaplan–Meier Survival Analyses in SPSS......Page 425 Comparing Two Survival Curves – the Mantel–Cox Test......Page 428 Mantel–Cox Using SPSS......Page 430 Hazard......Page 431 Hazard Functions in SPSS......Page 432 Writing Up a Survival Analysis......Page 433 Multiple Choice Questions......Page 434 Answers to Activities and Exercises......Page 439 Glossary......Page 470 References......Page 478 Index......Page 482