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Statistics for the Health Sciences : A Non-Mathematical Introduction - Professor Christine Dancey

Statistics for the Health Sciences

A Non-Mathematical Introduction

Paperback Published: 19th March 2012
ISBN: 9781849203364
Number Of Pages: 584

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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.

Industry Reviews

'Statistics for the Health Sciences engagingly presents the key analytic issues that students and professionals need to understand in the most accessible and vivid way possible. Full of real examples and practical exercises, the book successfully avoids getting bogged down with complex maths and formulae' -
Dennis Howitt at Loughborough University

The chapter overviews, absence of statistical formulae and use of appropriate examples and student exercises make this a very 'hands on' and practical text' -

Merryl E Harvey, Birmingham City University

About the Authorsp. xiii
Prefacep. xv
Acknowledgementsp. xvii
Companion Websitep. xix
An Introduction to the Research Processp. 1
Overviewp. 1
The Research Processp. 3
Concepts and Variablesp. 5
Levels of Measurementp. 8
Hypothesis Testingp. 10
Evidence-Based Practicep. 11
Research Designsp. 11
Summaryp. 18
Multiple Choice Questionsp. 18
Computer-Assisted Analysisp. 21
Overviewp. 21
Overview of the Three Statistical Packagesp. 22
Introduction to SPSSp. 26
Setting out Your Variables for Within- and Between-Group Designsp. 38
Introduction to Rp. 45
Introduction to SASp. 58
Summaryp. 71
Exercisesp. 72
Descriptive Statisticsp. 75
Overviewp. 75
Analysing Datap. 76
Descriptive Statisticsp. 77
Numerical Descriptive Statisticsp. 78
Choosing a Measure of Central Tendencyp. 82
Measures of Variation or Dispersionp. 82
Deviations from the Meanp. 85
Numerical Descriptives in SPSSp. 87
Graphical Statisticsp. 92
Bar Chartsp. 93
Line Graphsp. 101
Incorporating Variability into Graphsp. 104
Generating Graphs with Standard Deviations in SPSSp. 105
Graphs Showing Dispersion - Frequency Histogramp. 105
Box-Plotsp. 112
Summaryp. 117
SPSS Exercisep. 118
Multiple Choice Questionsp. 118
The Basis of Statistical Testingp. 122
Overviewp. 122
Introductionp. 123
Samples and Populationsp. 124
Distributionsp. 138
Statistical Significancep. 149
Criticisms of NHSTp. 151
Generating Confidence Intervals in SPSSp. 156
Summaryp. 161
SPSS Exercisep. 161
Multiple Choice Questionsp. 162
Epidemiologyp. 165
Overviewp. 165
Introductionp. 166
Estimating the Prevalence of Diseasep. 167
Difficulties in Estimating Prevalencep. 167
Beyond Prevalence: Identifying Risk Factors for Diseasep. 169
Risk Ratiosp. 170
The Odds-Ratiop. 171
Establishing Causalityp. 173
Case-Control Studiesp. 174
Cohort Studiesp. 176
Experimental Designsp. 178
Summaryp. 179
Multiple Choice Questionsp. 179
Introduction to Data Screening and Cleaningp. 182
Overviewp. 182
Introductionp. 183
Minimising Problems at the Design Stagep. 184
Entering Data into Databases/Statistical Packagesp. 185
The Dirty Datasetp. 186
Accuracyp. 186
Using Descriptive Statistics to Help Identify Errorsp. 186
Missing Datap. 189
Spotting Missing Datap. 194
Normalityp. 199
Screening Groups Separatelyp. 202
Reporting Data Screening and Cleaning Proceduresp. 202
Summaryp. 204
Multiple Choice Questionsp. 204
Differences Between Two Groupsp. 207
Overviewp. 207
Introductionp. 208
Conceptual Description of the t-Testsp. 210
Generalising to the Populationp. 213
Independent Groups t-Test in SPSSp. 214
Cohen's dp. 220
Paired t-Test in SPSSp. 222
Two-Sample z-Testp. 228
Non-Parametric Testsp. 230
Mann-Whitney: for Independent Groupsp. 230
Mann-Whitney Test in SPSSp. 230
Wilcoxon Signed Rank Test: for Repeated Measuresp. 237
Wilcoxon Signed Rank Test in SPSSp. 237
Adjusting for Multiple Testsp. 241
Summaryp. 241
Multiple Choice Questionsp. 241
Differences Between Three or More Conditionsp. 246
Overviewp. 246
Introductionp. 247
Conceptual Description of the (Parametric) ANOVAp. 249
One-Way ANOVAp. 250
One-way ANOVA in SPSSp. 252
ANOVA Models for Repeated-Measures Designsp. 258
Repeated-Measures ANOVA in SPSSp. 259
Non-Parametric Equivalentsp. 266
The Kruskal-Wallis Testp. 266
Kruskal-Wallis and the Median Test in SPSSp. 267
The Median Testp. 271
Friedman's ANOVA for Repeated Measuresp. 273
Friedman's ANOVA in SPSSp. 273
Summaryp. 278
Multiple Choice Questionsp. 278
Testing Associations Between Categorical Variablesp. 284
Overviewp. 284
Introductionp. 285
Rationale of Contingency Table Analysisp. 287
Running the Analysis in SPSSp. 288
Measuring Effect Size in Contingency Table Analysisp. 294
Larger Contingency Tablesp. 295
Contingency Table Analysis Assumptionsp. 296
The ¿2 Goodness-of-Fit Testp. 298
Running the ¿2 Goodness-of-Fit Test Using SPSSp. 300
Summaryp. 303
Multiple Choice Questionsp. 303
Measuring Agreement: Correlational Techniquesp. 307
Overviewp. 307
Introductionp. 308
Bivariate Relationshipsp. 309
Perfect Correlationsp. 314
Calculating the Correlation Pearson's r Using SPSSp. 317
How to Obtain Scatterplotsp. 320
Variance Explanation of rp. 325
Obtaining Correlational Analysis in SPSS: Exercisep. 327
Partial Correlationsp. 328
Shared and Unique Variance: Conceptual Understanding Relating to Partial Correlationsp. 331
Spearman's rhop. 333
Other Uses for Correlational Techniquesp. 335
Reliability of Measuresp. 336
Internal Consistencyp. 336
Inter-Rater Reliabilityp. 337
Validityp. 337
Percentage Agreementp. 337
Cohen's Kappap. 338
Summaryp. 338
Multiple Choice Questionsp. 339
Linear Regressionp. 345
Overviewp. 345
Introductionp. 346
Linear Regression in SPSSp. 351
Obtaining the Scatterplot with Regression Line and Confidence Intervals in SPSSp. 355
Assumptions Underlying Linear Regressionp. 363
Dealing with Outliersp. 363
What Happens if the Correlation between X and Y is Near Zero?p. 368
Using Regression to Predict Missing Data in SPSSp. 369
Prediction of Missing Scores on Cognitive Failures in SPSSp. 372
Summaryp. 374
Multiple Choice Questionsp. 375
Standard Multiple Regressionp. 379
Overviewp. 379
Introductionp. 380
Multiple Regression in SPSSp. 381
Variables in the Equationp. 384
The Regression Equationp. 387
Predicting an Individual's Scorep. 388
Hypothesis Testingp. 388
Other Types of Multiple Regressionp. 391
Hierarchical Multiple Regressionp. 394
Summaryp. 396
Multiple Choice Questionsp. 397
Logistic Regressionp. 402
Overviewp. 402
Introductionp. 403
The Conceptual Basis of Logistic Regressionp. 403
Writing up the Resultp. 413
Logistic Regression with Multiple Predictor Variablesp. 413
Logistic Regression with Categorical Predictorsp. 419
Categorical Predictors with Three or More Levelsp. 421
Summaryp. 424
Multiple Choice Questionsp. 424
Interventions and Analysis of Changep. 428
Overviewp. 428
Interventionsp. 429
How Do We Know Whether Interventions Are Effective?p. 429
Randomised Control Trials (RCTs)p. 432
Designing an RCT: CONSORTp. 433
The CONSORT Flow Chartp. 436
Important Features of an RCTp. 439
Blindingp. 443
Analysis of RCTsp. 444
Running an ANCOVA in SPSSp. 446
McNemar's Test of Changep. 448
Running McNemar's Test in SPSSp. 449
The Sign Testp. 452
Running the Sign Test Using SPSSp. 453
Intention to Treat Analysisp. 453
Crossover Designsp. 456
Single-Case Designs (N = 1)p. 457
Generating Single-Case Design Graphs Using SPSSp. 463
Summaryp. 468
SPSS Exercisep. 468
Multiple Choice Questionsp. 468
Survival Analysis: An Introductionp. 472
Overviewp. 472
Introductionp. 473
Survival Curvesp. 476
The Kaplan-Meier Survival Functionp. 482
Kaplan-Meier Survival Analyses in SPSSp. 484
Comparing Two Survival Curves - the Mantel-Cox Testp. 488
Mantel-Cox Using SPSSp. 490
Hazardp. 493
Hazard Curvesp. 493
Hazard Functions in SPSSp. 494
Writing Up a Survival Analysisp. 494
Summaryp. 495
SPSS Exercisep. 496
Multiple Choice Questionsp. 496
Answers to Activities and Exercisesp. 502
Glossaryp. 542
Referencesp. 552
Indexp. 558
Table of Contents provided by Ingram. All Rights Reserved.

ISBN: 9781849203364
ISBN-10: 1849203369
Audience: Tertiary; University or College
Format: Paperback
Language: English
Number Of Pages: 584
Published: 19th March 2012
Publisher: Sage Publications Ltd
Country of Publication: GB
Dimensions (cm): 22.23 x 18.42  x 2.54
Weight (kg): 1.0

Earn 198 Qantas Points
on this Book