Belinda Barton, Jennifer Peat

Medical Statistics (eBook, PDF)

A Guide to SPSS, Data Analysis and Critical Appraisal

• Format: PDF

Produktbeschreibung

Medical Statistics provides the necessary statistical tools to enable researchers to undertake and understand evidence-based clinical research. It is a practical guide to conducting statistical research and interpreting statistics in the context of how the participants were recruited, how the study was designed, what types of variables were used, what effect size was found, and what the P values mean. It guides researchers through the process of selecting the correct statistics and show how to best report results for presentation and publication. Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors' popular medical statistics courses. The table of contents is divided into sections according to whether data are continuous or categorical in nature as this distinction is fundamental to selecting the correct statistics. Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs. The chapters conclude with critical appraisal guidelines to help researchers review the reporting of results from each type of statistical test. This new edition includes a new chapter on repeated measures and mixed models and a helpful glossary of terms provides an easy reference that applies to all chapters.

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Produktdetails

• Verlag: For Dummies
• Seitenzahl: 408
• Erscheinungstermin: 6. August 2014
• Englisch
• ISBN-13: 9781118589915
• Artikelnr.: 41351692

Autorenporträt

Belinda Barton, Head and Psychologist, Children's Hospital Education Research Institute (CHERI), Conjoint Senior Lecturer, Sydney Medical School, University of Sydney, NSW Australia. Jennifer Peat, Associate Professor, Department of Paediatrics and Child Health and Senior Hospital Statistician, Clinical Epidemiology Unit, Children's Hospital, Westmead, NSW Australia.

Inhaltsangabe

Introduction
ix Acknowledgements
xiii About the companion website
xv Chapter 1 Creating an SPSS data file and preparing to analyse the data
1 1.1 Creating an SPSS data file
1 1.2 Opening data from Excel in SPSS
6 1.3 Categorical and continuous variables
7 1.4 Classifying variables for analyses
7 1.5 Hypothesis testing and P values
8 1.6 Choosing the correct statistical test
9 1.7 Sample size requirements
10 1.8 Study handbook and data analysis plan
12 1.9 Documentation
13 1.10 Checking the data
13 1.11 Avoiding and replacing missing values
14 1.12 SPSS data management capabilities
16 1.13 Managing SPSS output
20 1.14 SPSS help commands
21 1.15 Golden rules for reporting numbers
21 1.16 Notes for critical appraisal
21 References
23 Chapter 2 Descriptive statistics
24 2.1 Parametric and non-parametric statistics
25 2.2 Normal distribution
25 2.3 Skewed distributions
26 2.4 Checking for normality
29 2.5 Transforming skewed variables
43 2.6 Data analysis pathway
49 2.7 Reporting descriptive statistics
49 2.8 Checking for normality in published results
50 2.9 Notes for critical appraisal
51 References
51 Chapter 3 Comparing two independent samples
52 3.1 Comparing the means of two independent samples
52 3.2 One- and two-sided tests of significance
54 3.3 Effect sizes
55 3.4 Study design
57 3.5 Influence of sample size
58 3.6 Two-sample t-test
71 3.7 Confidence intervals
73 3.8 Reporting the results from two-sample t-tests
75 3.9 Rank-based non-parametric tests
80 3.10 Notes for critical appraisal
88 References
89 Chapter 4 Paired and one-sample t-tests
90 4.1 Paired t-tests
90 4.2 Non-parametric test for paired data
97 4.3 Standardizing for differences in baseline measurements
99 4.4 Single-sample t-test
102 4.5 Testing for a between-group difference
106 4.6 Notes for critical appraisal
110 References
111 Chapter 5 Analysis of variance
112 5.1 Building ANOVA and ANCOVA models
113 5.2 ANOVA models
113 5.3 One-way analysis of variance
117 5.4 Effect size for ANOVA
127 5.5 Post-hoc tests for ANOVA
128 5.6 Testing for a trend
133 5.7 Reporting the results of a one-way ANOVA
134 5.8 Factorial ANOVA models
135 5.9 An example of a three-way ANOVA
140 5.10 Analysis of covariance (ANCOVA)
145 5.11 Testing the model assumptions of ANOVA/ANCOVA
149 5.12 Reporting the results of an ANCOVA
158 5.13 Notes for critical appraisal
158 References
160 Chapter 6 Analyses of longitudinal data
161 6.1 Study design
161 6.2 Sample size and power
162 6.3 Covariates
163 6.4 Assumptions of repeated measures ANOVA and mixed models
163 6.5 Repeated measures analysis of variance
164 6.6 Linear mixed models
182 6.7 Notes for critical appraisal
195 References
196 Chapter 7 Correlation and regression
197 7.1 Correlation coefficients
197 7.2 Regression models
205 7.3 Multiple linear regression
213 7.4 Interactions
230 7.5 Residuals
235 7.6 Outliers and remote points
237 7.7 Validating the model
240 7.8 Reporting a multiple linear regression
241 7.9 Non-linear regression
242 7.10 Centering
244 7.11 Notes for critical appraisal
247 References
247 Chapter 8 Rates and proportions
249 8.1 Summarizing categorical variables
249 8.2 Describing baseline characteristics
251 8.3 Incidence and prevalence
252 8.4 Chi-square tests
253 8.5 2 × 3 Chi-square tables
260 8.6 Cells with small numbers
262 8.7 Exact chi square test
263 8.8 Number of cells that can be tested
264 8.9 Reporting chi-square tests and proportions
266 8.10 Large contingency tables
267 8.11 Categorizing continuous variables
271 8.12 Chi-square trend test for ordered variables
273 8.13 Number needed to treat (NNT)
277 8.14 Paired categorical variables: McNemar's chi-square test
281 8.15 Notes for critical appraisal
285 References
286 Chapter 9 Risk statistics
287 9.1 Risk statistics
287 9.2 Study design
288 9.3 Odds ratio
288 9.4 Protective odds ratios
296 9.5 Adjusted odds ratios
298 9.6 Relative risk
308 9.7 Number needed to be exposed for one additional person to be harmed (NNEH)
312 9.8 Notes for critical appraisal
312 References
313 Chapter 10 Tests of reliability and agreement
314 10.1 Reliability and agreement
314 10.2 Kappa statistic
317 10.3 Reliability of continuous measurements
321 10.4 Intra-class correlation
322 10.5 Measures of agreement
325 10.6 Notes for critical appraisal
329 References
329 Chapter 11 Diagnostic statistics
331 11.1 Coding for diagnostic statistics
331 11.2 Positive and negative predictive values
332 11.3 Sensitivity and specificity
335 11.4 Likelihood ratio
338 11.5 Receiver Operating Characteristic (ROC) Curves
339 11.6 Notes for critical appraisal
348 References
349 Chapter 12 Survival analyses
350 12.1 Study design
351 12.2 Censored observations
351 12.3 Kaplan-Meier survival method
351 12.4 Cox regression
360 12.5 Questions for critical appraisal
368 References
368 Glossary
370 Useful websites
381 Index
385