A Practical Approach to Using Statistics in Health Research: From Planning to Reporting

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  • Authors: Adam Mackridge, Philip Rowe
  • ISBN: 9781119383574
  • Publisher: John Wiley and Sons Ltd
  • Publication Date: June 08, 2018
  • Format: Hardback – 240 pages
  • Language: English

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Description

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.

Table of Contents
  1. Introduction 1
    1. At Whom is This Book Aimed? 1
    2. At What Scale of Project is This Book Aimed? 2
    3. Why Might This Book be Useful for You? 2
    4. How to Use This Book 3
    5. Computer Based Statistics Packages 4
    6. Relevant Videos etc. 5
  2. Data Types 7
    1. What Types of Data are There and Why Does it Matter? 7
    2. Continuous Measured Data 7
    3. Continuous Measured Data – Normal and Non‐Normal Distribution 8
    4. Transforming Non‐Normal Data 13
    5. Ordinal Data 13
    6. Categorical Data 14
    7. Ambiguous Cases 14
    8. A Continuously Varying Measure that has been Divided into a Small Number of Ranges 14
    9. Composite Scores with a Wide Range of Possible Values 15
    10. Relevant Videos etc. 15
  3. Presenting and Summarizing Data 17
    1. Continuous Measured Data 17
    2. Normally Distributed Data – Using the Mean and Standard Deviation 18
    3. Data With Outliers, e.g. Skewed Data – Using Quartiles and the Median 18
    4. Polymodal Data – Using the Modes 20
    5. Ordinal Data 21
    6. Ordinal Scales With a Narrow Range of Possible Values 22
    7. Ordinal Scales With a Wide Range of Possible Values 22
    8. Dividing an Ordinal Scale Into a Small Number of Ranges (e.g. Satisfactory/Unsatisfactory or Poor/Acceptable/Good) 22
    9. Summary for Ordinal Data 23
    10. Categorical Data 23
    11.  Relevant Videos etc. 24
    12. 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
    1. Identify the Factor and Outcome 27
    2. Identify the Type of Data Used to Record the Relevant Factor 29
    3. Statistical Methods Where the Factor is Categorical 30
    4. Identify the Type of Data Used to Record the Outcome 30
    5. Is Continuous Measured Outcome Data Normally Distributed or Can It Be Transformed to Normality? 30
    6. Identify Whether Your Sets of Outcome Data Are Related or Independent 31
    7. For the Factor, How Many Levels Are Being Studied? 32
    8. Determine the Appropriate Statistical Method for Studies with a Categorical Factor 32
    9. Correlation and Regression with a Measured Factor 34
    10. What Type of Data Was Used to Record Your Factor and Outcome? 34
    11. When Both the Factor and the Outcome Consist of Continuous Measured Values, Select Between Pearson and Spearman Correlation 34
    12. Relevant Additional Material 38
  5. Multiple Testing 39
    1. What Is Multiple Testing and Why Does It Matter? 39
    2. What Can We Do to Avoid an Excessive Risk of False Positives? 40
    3. Use of Omnibus Tests 40
    4. Distinguishing Between Primary and Secondary/ Exploratory Analyses 40
    5. Bonferroni Correction 41
  6. Common Issues and Pitfalls 43
    1. Determining Equality of Standard Deviations 43
    2. How Do I Know, in Advance, How Large My SD Will Be? 43
    3. One‐Sided Versus Two‐Sided Testing 44
    4. Pitfalls That Make Data Look More Meaningful Than It Really Is 45
    5. Too Many Decimal Places 45
    6. Percentages with Small Sample Sizes 47
    7. Discussion of Statistically Significant Results 47
    8. Discussion of Non‐Significant Results 50
    9. Describing Effect Sizes with Non‐Parametric Tests 51
    10. Confusing Association with a Cause and Effect Relationship 52
  7. Contingency Chi‐Square Test 55
    1. When Is the Test Appropriate? 55
    2. An Example 55
    3. Presenting the Data 57
    4. Contingency Tables 57
    5. Clustered or Stacked Bar Charts 57
    6. Data Requirements 59
    7. An Outline of the Test 59
    8. Planning Sample Sizes 59
    9. Carrying Out the Test 60
    10. Special Issues 61
    11. Yates Correction 61
    12. Low Expected Frequencies – Fisher’s Exact Test 61
    13. Describing the Effect Size 61
    14. Absolute Risk Difference (ARD) 62
    15. Number Needed to Treat (NNT) 63
    16. Risk Ratio (RR) 63
    17. Odds Ratio (OR) 64
    18. Case: Control Studies 65
    19. How to Report the Analysis 65
    20. Methods 65
    21. Results 66
    22. Discussion 67
    23. Confounding and Logistic Regression 67
    24. Reporting the Detection of Confounding 68
    25. Larger Tables 69
    26. Collapsing Tables 69
    27. Reducing Tables 70
    28. Relevant Videos etc. 71
  8. Independent Samples (Two‐Sample) T‐Test 73
    1. When Is the Test Applied? 73
    2. An Example 73
    3. Presenting the Data 75
    4. Numerically 75
    5. Graphically 75
    6. Data Requirements 75
    7. Variables Required 75
    8. Normal Distribution of the Outcome Variable Within the Two Samples 75
    9. Equal Standard Deviations 78
    10. Equal Sample Sizes 78
    11. An Outline of the Test 78
    12. Planning Sample Sizes 79
    13. Carrying Out the Test 79
    14. Describing the Effect Size 79
    15. How to Describe the Test, the Statistical and Practical Significance of Your Findings in Your Report 80
    16. Methods Section 80
    17. Results Section 80
    18. Discussion Section 81
    19. Relevant Videos etc. 81
  9. Mann–Whitney Test 83
    1. When Is the Test Applied? 83
    2. An Example 83
    3. Presenting the Data 85
    4. Numerically 85
    5. Graphically 85
    6. Divide the Outcomes into Low and High Ranges 85
    7. Data Requirements 86
    8. Variables Required 86
    9. Normal Distributions and Equality of Standard Deviations 87
    10. Equal Sample Sizes 87
    11. An Outline of the Test 87
    12. Statistical Significance 87
    13. Planning Sample Sizes 87
    14. Carrying Out the Test 88
    15. Describing the Effect Size 88
    16. How to Report the Test 89
    17. Methods Section 89
    18. Results Section 89
    19. Discussion Section 90
    20. Relevant Videos etc. 91
  10. One‐Way Analysis of Variance (ANOVA) – Including Dunnett’s and Tukey’s Follow Up Tests 93
    1. When Is the Test Applied? 93
    2. An Example 93
    3. Presenting the Data 94
    4. Numerically 94
    5. Graphically 94
    6. Data Requirements 94
    7. Variables Required 94
    8. Normality of Distribution for the Outcome Variable Within the Three Samples 95
    9. Standard Deviations 96
    10. Sample Sizes 98
    11. An Outline of the Test 98
    12. Follow Up Tests 98
    13. Planning Sample Sizes 99
    14. Carrying Out the Test 100
    15. Describing the Effect Size 101
    16. How to Report the Test 101
    17. Methods 101
    18. Results Section 102
    19. Discussion Section 102
    20. Relevant Videos etc. 103
  11. Kruskal–Wallis 105
    1. When Is the Test Applied? 105
    2. An Example 105
    3. Presenting the Data 106
    4. Numerically 106
    5. Graphically 107
    6. Data Requirements 109
    7. Variables Required 109
    8. Normal Distributions and Standard Deviations 109
    9. Equal Sample Sizes 110
    10. An Outline of the Test 110
    11. Planning Sample Sizes 110
    12. Carrying Out the Test 110
    13. Describing the Effect Size 111
    14. Determining Which Group Differs from Which Other 111
    15. How to Report the Test 111
    16. Methods Section 111
    17. Results Section 112
    18. Discussion Section 113
    19. Relevant Videos etc. 114
  12. McNemar’s Test 115
    1. When Is the Test Applied? 115
    2. An Example 115
    3. Presenting the Data 116
    4. Data Requirements 116
    5. An Outline of the Test 118
    6. Planning Sample Sizes 118
    7. Carrying Out the Test 119
    8. Describing the Effect Size 119
    9. How to Report the Test 119
    10. Methods Section 119
    11. Results Section 120
    12. Discussion Section 120
    13. Relevant Videos etc. 121
  13. Paired T‐Test 123
    1. When Is the Test Applied? 123
    2. An Example 125
    3. Presenting the Data 125
    4. Numerically 125
    5. Graphically 125
    6. Data Requirements 126
    7. Variables Required 126
    8. Normal Distribution of the Outcome Data 126
    9. Equal Standard Deviations 128
    10. Equal Sample Sizes 128
    11. An Outline of the Test 128
    12. Planning Sample Sizes 129
    13. Carrying Out the Test 129
    14. Describing the Effect Size 129
    15. How to Report the Test 130
    16. Methods Section 130
    17. Results Section 130
    18. Discussion Section 131
    19. Relevant Videos etc. 131
  14. Wilcoxon Signed Rank Test 133
    1. When Is the Test Applied? 133
    2. An Example 134
    3. Presenting the Data 134
    4. Numerically 134
    5. Graphically 136
    6. Data Requirements 136
    7. Variables Required 136
    8. Normal Distributions and Equal Standard Deviations 137
    9. Equal Sample Sizes 137
    10. An Outline of the Test 137
    11. Planning Sample Sizes 138
    12. Carrying Out the Test 139
    13. Describing the Effect Size 139
    14. How to Report the Test 140
    15. Methods Section 140
    16. Results Section 140
    17. Discussion Section 141
    18. Relevant Videos etc. 141
  15. Repeated Measures Analysis of Variance 143
    1. When Is the Test Applied? 143
    2. An Example 144
    3. Presenting the Data 144
    4. Numerical Presentation of the Data 145
    5. Graphical Presentation of the Data 145
    6. Data Requirements 146
    7. Variables Required 146
    8. Normal Distribution of the Outcome Data 148
    9. Equal Standard Deviations 148
    10. Equal Sample Sizes 148
    11. An Outline of the Test 148
    12. Planning Sample Sizes 149
    13. Carrying Out the Test 150
    14. Describing the Effect Size 150
    15. How to Report the Test 151
    16. Methods Section 151
    17. Results Section 151
    18. Discussion Section 152
    19. Relevant Videos etc. 153
  16. Friedman Test 155
    1. When Is the Test Applied? 15516.2
    2. An Example 157
    3. Presenting the Data 157
    4. Bar Charts of the Outcomes at Various Stages 157
    5. Summarizing the Data via Medians or Means 157
    6. Splitting the Data at Some Critical Point in the Scale 159
    7. Data Requirements 160
    8. Variables Required 160
    9. Normal Distribution and Standard Deviations in the Outcome Data 160
    10. Equal Sample Sizes 160
    11. An Outline of the Test 160
    12. Planning Sample Sizes 161
    13. Follow Up Tests 161
    14. Carrying Out the Tests 162
    15. Describing the Effect Size 162
    16. Median or Mean Values Among the Individual Changes 162
    17. Split the Scale 162
    18. How to Report the Test 162
    19. Methods Section 162
    20. Results Section 163
    21. Discussion Section 164
    22. Relevant Videos etc. 164
  17. Pearson Correlation 165
    1. Presenting the Data 165
    2. Correlation Coefficient and Statistical Significance 166
    3. Planning Sample Sizes 167
    4. Effect Size and Practical Relevance 167
    5. Regression 169
    6. How to Report the Analysis 170
    7. Methods 170
    8. Results 170
    9. Discussion 171
    10. Relevant Videos etc. 171
  18. Spearman Correlation 173
    1. Presenting the Data 173
    2. Testing for Evidence of Inappropriate Distributions 174
    3. Rho and Statistical Significance 174
    4. An Outline of the Significance Test 175
    5. Planning Sample Sizes 175
    6. Effect Size 176
    7. Where Both Measures Are Ordinal 176
    8. Educational Level and Willingness to Undertake Internet Research – An Example Where Both Measures Are Ordinal 176
    9. Presenting the Data 177
    10. Rho and Statistical Significance 177
    11. Effect Size 178
    12. How to Report Spearman Correlation Analyses 178
    13. Methods 178
    14. Results 179
    15. Discussion 180
    16. Relevant Videos etc. 180
  19. Logistic Regression 181
    1. Use of Logistic Regression with Categorical Outcomes 181
    2. An Outline of the Significance Test 182
    3. Planning Sample Sizes 182
    4. Results of the Analysis 184
    5. Describing the Effect Size 184
    6. How to Report the Analysis 185
    7. Methods 185
    8. Results 186
    9. Discussion 186
    10. Relevant Videos etc. 187
  20. Cronbach’s Alpha 189
    1. Appropriate Situations for the Use of Cronbach’s Alpha 18920.2
    2. Inappropriate Uses of Alpha 190
    3. Interpretation 190
    4. Reverse Scoring 191
    5. An Example 191
    6. Performing and Interpreting the Analysis 192
    7. How to Report Cronbach’s Alpha Analyses 193
    8. Methods Section 193
    9. Results 194
    10. Discussion 194
    11. Relevant Videos etc. 195
    12. Glossary 197
    13. Videos 209
    14. Index 211
Author Biography

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.

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