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A Practical Approach to Using Statistics in Health Research: From Planning to Reporting
ISBN-13: 9781119383574 / Angielski / Twarda / 2018 / 240 str.
A Practical Approach to Using Statistics in Health Research: From Planning to Reporting
ISBN-13: 9781119383574 / Angielski / Twarda / 2018 / 240 str.
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A hands-on guide to using statistics in health research, from planning, through analysis, and on to reporting A Practical Approach to Using Statistics in Health Research offers an easy to use, step-by-step guide for using statistics in health research.
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About the Companion Website xv
1 Introduction 1
1.1 At Whom is This Book Aimed? 1
1.2 At What Scale of Project is This Book Aimed? 2
1.3 Why Might This Book be Useful for You? 2
1.4 How to Use This Book 3
1.5 Computer Based Statistics Packages 4
1.6 Relevant Videos etc. 5
2 Data Types 7
2.1 What Types of Data are There and Why Does it Matter? 7
2.2 Continuous Measured Data 7
2.3 Ordinal Data 13
2.4 Categorical Data 14
2.5 Ambiguous Cases 14
2.6 Relevant Videos etc. 15
3 Presenting and Summarizing Data 17
3.1 Continuous Measured Data 17
3.2 Ordinal Data 21
3.3 Categorical Data 23
3.4 Relevant Videos etc. 24
Appendix 1: An Example of the Insensitivity of the Median When Used to Describe Data from an Ordinal Scale With a Narrow Range of Possible Values 25
4 Choosing a Statistical Test 27
4.1 Identify the Factor and Outcome 27
4.2 Identify the Type of Data Used to Record the Relevant Factor 29
4.3 Statistical Methods Where the Factor is Categorical 30
4.4 Correlation and Regression with a Measured Factor 34
4.5 Relevant Additional Material 38
5 Multiple Testing 39
5.1 What Is Multiple Testing and Why Does It Matter? 39
5.2 What Can We Do to Avoid an Excessive Risk of False Positives? 40
6 Common Issues and Pitfalls 43
6.1 Determining Equality of Standard Deviations 43
6.2 How Do I Know, in Advance, How Large My SD Will Be? 43
6.3 One ]Sided Versus Two ]Sided Testing 44
6.4 Pitfalls That Make Data Look More Meaningful Than It Really Is 45
6.5 Discussion of Statistically Significant Results 47
6.6 Discussion of Non ]Significant Results 50
6.7 Describing Effect Sizes with Non ]Parametric Tests 51
6.8 Confusing Association with a Cause and Effect Relationship 52
7 Contingency Chi ]Square Test 55
7.1 When Is the Test Appropriate? 55
7.2 An Example 55
7.3 Presenting the Data 57
7.4 Data Requirements 59
7.5 An Outline of the Test 59
7.6 Planning Sample Sizes 59
7.7 Carrying Out the Test 60
7.8 Special Issues 61
7.9 Describing the Effect Size 61
7.10 How to Report the Analysis 65
7.11 Confounding and Logistic Regression 67
7.12 Larger Tables 69
8 Independent Samples (Two ]Sample) T ]Test 73
8.1 When Is the Test Applied? 73
8.2 An Example 73
8.3 Presenting the Data 75
8.4 Data Requirements 75
8.5 An Outline of the Test 78
8.6 Planning Sample Sizes 79
8.7 Carrying Out the Test 79
8.8 Describing the Effect Size 79
8.9 How to Describe the Test, the Statistical and Practical Significance of Your Findings in Your Report 80
8.10 Relevant Videos etc. 81
9 Mann Whitney Test 83
9.1 When Is the Test Applied? 83
9.2 An Example 83
9.3 Presenting the Data 85
9.4 Data Requirements 86
9.5 An Outline of the Test 87
9.6 Statistical Significance 87
9.7 Planning Sample Sizes 87
9.8 Carrying Out the Test 88
9.9 Describing the Effect Size 88
9.10 How to Report the Test 89
9.11 Relevant Videos etc. 91
10 One ]Way Analysis of Variance (ANOVA) Including Dunnett s and Tukey s Follow Up Tests 93
10.1 When Is the Test Applied? 93
10.2 An Example 93
10.3 Presenting the Data 94
10.4 Data Requirements 94
10.5 An Outline of the Test 98
10.6 Follow Up Tests 98
10.7 Planning Sample Sizes 99
10.8 Carrying Out the Test 100
10.9 Describing the Effect Size 101
10.10 How to Report the Test 101
10.11 Relevant Videos etc. 103
11 Kruskal Wallis 105
11.1 When Is the Test Applied? 105
11.2 An Example 105
11.3 Presenting the Data 106
11.4 Data Requirements 109
11.5 An Outline of the Test 110
11.6 Planning Sample Sizes 110
11.7 Carrying Out the Test 110
11.8 Describing the Effect Size 111
11.9 Determining Which Group Differs from Which Other 111
11.10 How to Report the Test 111
11.11 Relevant Videos etc. 114
12 McNemar s Test 115
12.1 When Is the Test Applied? 115
12.2 An Example 115
12.3 Presenting the Data 116
12.4 Data Requirements 116
12.5 An Outline of the Test 118
12.6 Planning Sample Sizes 118
12.7 Carrying Out the Test 119
12.8 Describing the Effect Size 119
12.9 How to Report the Test 119
12.10 Relevant Videos etc. 121
13 Paired T ]Test 123
13.1 When Is the Test Applied? 123
13.2 An Example 125
13.3 Presenting the Data 125
13.4 Data Requirements 126
13.5 An Outline of the Test 128
13.6 Planning Sample Sizes 129
13.7 Carrying Out the Test 129
13.8 Describing the Effect Size 129
13.9 How to Report the Test 130
13.10 Relevant Videos etc. 131
14 Wilcoxon Signed Rank Test 133
14.1 When Is the Test Applied? 133
14.2 An Example 134
14.3 Presenting the Data 134
14.4 Data Requirements 136
14.5 An Outline of the Test 137
14.6 Planning Sample Sizes 138
14.7 Carrying Out the Test 139
14.8 Describing the Effect Size 139
14.9 How to Report the Test 140
14.10 Relevant Videos etc. 141
15 Repeated Measures Analysis of Variance 143
15.1 When Is the Test Applied? 143
15.2 An Example 144
15.3 Presenting the Data 144
15.4 Data Requirements 146
15.5 An Outline of the Test 148
15.6 Planning Sample Sizes 149
15.7 Carrying Out the Test 150
15.8 Describing the Effect Size 150
15.9 How to Report the Test 151
15.10 Relevant Videos etc. 153
16 Friedman Test 155
16.1 When Is the Test Applied? 155
16.2 An Example 157
16.3 Presenting the Data 157
16.4 Data Requirements 160
16.5 An Outline of the Test 160
16.6 Planning Sample Sizes 161
16.7 Follow Up Tests 161
16.8 Carrying Out the Tests 162
16.9 Describing the Effect Size 162
16.10 How to Report the Test 162
16.11 Relevant Videos etc. 164
17 Pearson Correlation 165
17.1 Presenting the Data 165
17.2 Correlation Coefficient and Statistical Significance 166
17.3 Planning Sample Sizes 167
17.4 Effect Size and Practical Relevance 167
17.5 Regression 169
17.6 How to Report the Analysis 170
17.7 Relevant Videos etc. 171
18 Spearman Correlation 173
18.1 Presenting the Data 173
18.2 Testing for Evidence of Inappropriate Distributions 174
18.3 Rho and Statistical Significance 174
18.4 An Outline of the Significance Test 175
18.5 Planning Sample Sizes 175
18.6 Effect Size 176
18.7 Where Both Measures Are Ordinal 176
18.8 How to Report Spearman Correlation Analyses 178
18.9 Relevant Videos etc. 180
19 Logistic Regression 181
19.1 Use of Logistic Regression with Categorical Outcomes 181
19.2 An Outline of the Significance Test 182
19.3 Planning Sample Sizes 182
19.4 Results of the Analysis 184
19.5 Describing the Effect Size 184
19.6 How to Report the Analysis 185
19.7 Relevant Videos etc. 187
20 Cronbach s Alpha 189
20.1 Appropriate Situations for the Use of Cronbach s Alpha 189
20.2 Inappropriate Uses of Alpha 190
20.3 Interpretation 190
20.4 Reverse Scoring 191
20.5 An Example 191
20.6 Performing and Interpreting the Analysis 192
20.7 How to Report Cronbach s Alpha Analyses 193
20.7 Relevant Videos etc. 195
Glossary 197
Videos 209
Index 211
Adam Mackridge, Ph.D., is a Research Pharmacist at Betsi Cadwaladr University Health Board in North Wales. He has over 15 years of experience in planning, conducting and reporting health research. He received his PhD in Pharmacy Practice from Aston University in Birmingham, UK.
Philip Rowe, Ph.D., is a Visiting Research Fellow in the School of Pharmacy and Molecular Sciences at Liverpool John Moores University, Liverpool, UK. He is a Fellow of the Royal Statistical Society and has authored other statistically based books for Wiley.
A Hands–On Guide to Using Statistics in Health Research, from Planning, through Analysis, and on to Reporting
A Practical Approach to Using Statistics in Health Research offers an easy to use, step–by–step guide for using statistics in health research. The authors use their experience of statistics and health research to explain how statistics fit in to all stages of the research process. They explain how to determine necessary sample sizes, interpret whether there are statistically significant difference in outcomes between groups, and use measured effect sizes to decide whether any changes are large enough to be relevant to professional practice.
The text walks you through how to identify the main outcome measure for your study and the factor which you think may influence that outcome and then determine what type of data will be used to record both of these. It then describes how this information is used to select the most appropriate methods to report and analyze your data. A step–by–step guide on how to use a range of common statistical procedures are then presented in separate chapters. To help you make sure that you are using statistics robustly, the authors also explore topics such as multiple testing and how to check whether measured data follows a normal distribution. Videos showing how to use computer packages to carry out all the various methods mentioned in the book are available on our companion web site. This book:
- Covers statistical aspects of all the stages of health research from planning to final reporting
- Explains how to report statistical planning, how analyses were performed, and the results and conclusion
- Puts the spotlight on consideration of clinical significance and not just statistical significance
- Explains the importance of reporting 95% confidence intervals for effect size
- Includes a systematic guide for selection of statistical tests and uses example data sets and videos to help you understand exactly how to use statistics
Written as an introductory guide to statistics for healthcare professionals, students and lecturers in the fields of pharmacy, nursing, medicine, dentistry, physiotherapy, and occupational therapy, A Practical Approach to Using Statistics in Health Research: From Planning to Reporting is a handy reference that focuses on the application of statistical methods within the health research context.
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