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

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A Practical Approach to Using Statistics in Health Research: From Planning to Reporting Vital Source e-bog

Adam Mackridge og Philip Rowe
(2018)
John Wiley & Sons
1.257,00 kr.
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A Practical Approach to Using Statistics in Health Research - From Planning to Reporting

A Practical Approach to Using Statistics in Health Research

From Planning to Reporting
Adam Mackridge og Philip Rowe
(2018)
Sprog: Engelsk
John Wiley & Sons, Limited
1.378,00 kr.
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Detaljer om varen

  • 1. Udgave
  • Vital Source searchable e-book (Reflowable pages)
  • Udgiver: John Wiley & Sons (April 2018)
  • Forfattere: Adam Mackridge og Philip Rowe
  • ISBN: 9781119383611
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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Detaljer om varen

  • Hardback: 240 sider
  • Udgiver: John Wiley & Sons, Limited (Juni 2018)
  • Forfattere: Adam Mackridge og Philip Rowe
  • ISBN: 9781119383574

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. 

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
2.2.1 Continuous Measured Data - Normal and NonNormal Distribution 8
2.2.2 Transforming NonNormal Data 13
2.3 Ordinal Data 13
2.4 Categorical Data 14
2.5 Ambiguous Cases 14
2.5.1 A Continuously Varying Measure that has been Divided into a Small Number of Ranges 14
2.5.2 Composite Scores with a Wide Range of Possible Values 15
2.6 Relevant Videos etc. 15 3 Presenting and Summarizing Data 17
3.1 Continuous Measured Data 17
3.1.1 Normally Distributed Data - Using the Mean and Standard Deviation 18
3.1.2 Data With Outliers, e.g. Skewed Data - Using Quartiles and the Median 18
3.1.3 Polymodal Data - Using the Modes 20
3.2 Ordinal Data 21
3.2.1 Ordinal Scales With a Narrow Range of Possible Values 22
3.2.2 Ordinal Scales With a Wide Range of Possible Values 22
3.2.3 Dividing an Ordinal Scale Into a Small Number of Ranges (e.g. Satisfactory/Unsatisfactory or Poor/Acceptable/Good) 22
3.2.4 Summary for Ordinal Data 23
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
4.3.1 Identify the Type of Data Used to Record the Outcome 30
4.3.2 Is Continuous Measured Outcome Data Normally Distributed or Can It Be Transformed to Normality? 30
4.3.3 Identify Whether Your Sets of Outcome Data Are Related or Independent 31
4.3.4 For the Factor, How Many Levels Are Being Studied? 32
4.3.5 Determine the Appropriate Statistical Method for Studies with a Categorical Factor 32
4.4 Correlation and Regression with a Measured Factor 34
4.4.1 What Type of Data Was Used to Record Your Factor and Outcome? 34
4.4.2 When Both the Factor and the Outcome Consist of Continuous Measured Values, Select Between Pearson and Spearman Correlation 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
5.2.1 Use of Omnibus Tests 40
5.2.2 Distinguishing Between Primary and Secondary/ Exploratory Analyses 40
5.2.3 Bonferroni Correction 41 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 OneSided Versus TwoSided Testing 44
6.4 Pitfalls That Make Data Look More Meaningful Than It Really Is 45
6.4.1 Too Many Decimal Places 45
6.4.2 Percentages with Small Sample Sizes 47
6.5 Discussion of Statistically Significant Results 47
6.6 Discussion of NonSignificant Results 50
6.7 Describing Effect Sizes with NonParametric Tests 51
6.8 Confusing Association with a Cause and Effect Relationship 52 7 Contingency ChiSquare Test 55
7.1 When Is the Test Appropriate? 55
7.2 An Example 55
7.3 Presenting the Data 57
7.3.1 Contingency Tables 57
7.3.2 Clustered or Stacked Bar Charts 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
7.8.1 Yates Correction 61
7.8.2 Low Expected Frequencies - Fisher''s Exact Test 61
7.9 Describing the Effect Size 61
7.9.1 Absolute Risk Difference (ARD) 62
7.9.2 Number Needed to Treat (NNT) 63
7.9.3 Risk Ratio (RR) 63
7.9.4 Odds Ratio (OR) 64
7.9.5 Case: Control Studies 65
7.10 How to Report the Analysis 65
7.10.1 Methods 65
7.10.2 Results 66
7.10.3 Discussion 67
7.11 Confounding and Logistic Regression 67
7.11.1 Reporting the Detection of Confounding 68
7.12 Larger Tables 69
7.12.1 Collapsing Tables 69 7
12.2 Reducing Tables 70
7.13 Relevant Videos etc. 71 8 Independent Samples (TwoSample) TTest 73
8.1 When Is the Test Applied? 73
8.2 An Example 73
8.3 Presenting the Data 75
8.3.1 Numerically 75
8.3.2 Graphically 75
8.4 Data Requirements 75
8.4.1 Variables Required 75
8.4.2 Normal Distribution of the Outcome Variable Within the Two Samples 75
8.4.3 Equal Standard Deviations 78
8.4.4 Equal Sample Sizes 78
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
8.9.1 Methods Section 80
8.9.2 Results Section 80
8.9.3 Discussion Section 81
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
9.3.1 Numerically 85
9.3.2 Graphically 85
9.3.3 Divide the Outcomes into Low and High Ranges 85
9.4 Data Requirements 86
9.4.1 Variables Required 86
9.4.2 Normal Distributions and Equality of Standard Deviations 87
9.4.3 Equal Sample Sizes 87
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
9.10.1 Methods Section 89
9.10.2 Results Section 89
9.10.3 Discussion Section 90
9.11 Relevant Videos etc. 91 10 OneWay 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
10.3.1 Numerically 94
10.3.2 Graphically 94
10.4 Data Requirements 94
10.4.1 Variables Required 94
10.4.2 Normality of Distribution for the Outcome Variable Within the Three Samples 95
10.4.3 Standard Deviations 96
10.4.4 Sample Sizes 98
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
10.10.1 Methods 101
10.10.2 Results Section 102
10.10.3 Discussion Section 102
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
11.3.1 Numerically 106
11.3.2 Graphically 107
11.4 Data Requirements 109
11.4.1 Variables Required 109
11.4.2 Normal Distributions and Standard Deviations 109
11.4.3 Equal Sample Sizes 110
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
11.10.1 Methods Section 111
11.10.2 Results Section 112
11.10.3 Discussion Section 113
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
12.9.1 Methods Section 119
12.9.2 Results Section 120
12.9.3 Discussion Section 120
12.10 Relevant Videos etc. 121 13 Paired TTest 123
13.1 When Is the Test Applied? 123
13.2 An Example 125
13.3 Presenting the Data 125
13.3.1 Numerically 125
13.3.2 Graphically 125
13.4 Data Requirements 126
13.4.1 Variables Required 126
13.4.2 Normal Distribution of the Outcome Data 126
13.4.3 Equal Standard Deviations 128
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