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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

Autorzy
Wydawnictwo John Wiley and Sons Ltd
Data wydania 16/04/2018
Liczba stron 240
Forma publikacji książka w twardej oprawie
Poziom zaawansowania Dla profesjonalistów, specjalistów i badaczy naukowych
ISBN 9781119383574
Kategorie Epidemiologia i statystyka medyczna, Matematyka
496.42 PLN (z VAT)
$132.86 / €110.86 / £99.70 /
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Opis książki

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.

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

Spis treści

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 Non?Normal Distribution 8


2.2.2 Transforming Non?Normal 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 One?Sided Versus Two?Sided 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 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


7.3.1 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 (Two?Sample) T?Test 73


8.1 When Is the Test Applied? 73


8.2 An Example 73


8.3 Presenting the Data 75


8.3.1 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 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


10.3.1 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 T?Test 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


13.4.4 Equal Sample Sizes 128


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


13.9.1 Methods Section 130


13.9.2 Results Section 130


13.9.3 Discussion Section 131


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


14.3.1 Numerically 134


14.3.2 Graphically 136


14.4 Data Requirements 136


14.4.1 Variables Required 136


14.4.2 Normal Distributions and Equal Standard Deviations 137


14.4.3 Equal Sample Sizes 137


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


14.9.1 Methods Section 140


14.9.2 Results Section 140


14.9.3 Discussion Section 141


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


15.3.1 Numerical Presentation of the Data 145


15.3.2 Graphical Presentation of the Data 145


15.4 Data Requirements 146


15.4.1 Variables Required 146


15.4.2 Normal Distribution of the Outcome Data 148


15.4.3 Equal Standard Deviations 148


15.4.4 Equal Sample Sizes 148


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


15.9.1 Methods Section 151


15.9.2 Results Section 151


15.9.3 Discussion Section 152


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


16.3.1 Bar Charts of the Outcomes at Various Stages 157


16.3.2 Summarizing the Data via Medians or Means 157


16.3.3 Splitting the Data at Some Critical Point in the Scale 159


16.4 Data Requirements 160


16.4.1 Variables Required 160


16.4.2 Normal Distribution and Standard Deviations in the Outcome Data 160


16.4.3 Equal Sample Sizes 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


16.9.1 Median or Mean Values Among the Individual Changes 162


16.9.2 Split the Scale 162


16.10 How to Report the Test 162


16.10.1 Methods Section 162


16.10.2 Results Section 163


16.10.3 Discussion Section 164


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


17.6.1 Methods 170


17.6.2 Results 170


17.6.3 Discussion 171


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


18.7.1 Educational Level and Willingness to Undertake Internet Research - An Example Where Both Measures Are Ordinal 176


18.7.2 Presenting the Data 177


18.7.3 Rho and Statistical Significance 177


18.7.4 Effect Size 178


18.8 How to Report Spearman Correlation Analyses 178


18.8.1 Methods 178


18.8.2 Results 179


18.8.3 Discussion 180


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


19.6.1 Methods 185


19.6.2 Results 186


19.6.3 Discussion 186


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


20.7.1 Methods Section 193


20.7.2 Results 194


20.7.3 Discussion 194


20.7 Relevant Videos etc. 195


Glossary 197


Videos 209


Index 211

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