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.
Author(s): Christine P. Dancey, John Reidy, Richard Rowe
Edition: Paperback
Publisher: Sage Publications
Year: 2012
Language: English
Pages: 563
Tags: Statistics, SPSS, Health Sciences, Medical Statistics, Data Interpretation
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
