A Practical Approach to Using Statistics in Health Research by Mackridge, Rowe

Description: A Practical Approach to Using Statistics in Health Research From Planning to Reportingby Adam Mackridge, Philip Rowe ISBN-13: 9781119383574 ISBN-10: 1119383579 Publisher: Wiley Binding: Hardcover Publication Year: 2018 Edition: First Condition: Very Good – clean pages • excellent About: refer to image(s)Contents:1 Introduction 1.1 At Whom is This Book Aimed? 1.2 At What Scale of Project is This Book Aimed? 1.3 Why Might This Book be Useful for You? 1.4 How to Use This Book 1.5 Computer Based Statistics Packages 1.6 Relevant Videos etc. 2 Data Types 2.1 What Types of Data are There and Why Does it Matter? 2.2 Continuous Measured Data 2.2.1 Continuous Measured Data — Normal and Non‐Normal Distribution 2.2.2 Transforming Non‐Normal Data 2.3 Ordinal Data 2.4 Categorical Data 2.5 Ambiguous Cases 2.5.1 A Continuously Varying Measure that has been Divided into a Small Number of Ranges 2.5.2 Composite Scores with a Wide Range of Possible Values 2.6 Relevant Videos etc. 3 Presenting and Summarizing Data 3.1 Continuous Measured Data 3.1.1 Normally Distributed Data — Using the Mean and Standard Deviation 3.1.2 Data With Outliers, e.g. Skewed Data — Using Quartiles and the Median 3.1.3 Polymodal Data — Using the Modes 3.2 Ordinal Data 3.2.1 Ordinal Scales With a Narrow Range of Possible Values 3.2.2 Ordinal Scales With a Wide Range of Possible Values 3.2.3 Dividing an Ordinal Scale Into a Small Number of Ranges 3.2.4 Summary for Ordinal Data 3.3 Categorical Data 3.4 Relevant Videos etc. 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 4 Choosing a Statistical Test 4.1 Identify the Factor and Outcome 4.2 Identify the Type of Data Used to Record the Relevant Factor 4.3 Statistical Methods Where the Factor is Categorical 4.3.1 Identify the Type of Data Used to Record the Outcome 4.3.2 Is Continuous Measured Outcome Data Normally Distributed or Can It Be Transformed to Normality? 4.3.3 Identify Whether Your Sets of Outcome Data Are Related or Independent 4.3.4 For the Factor, How Many Levels Are Being Studied? 4.3.5 Determine the Appropriate Statistical Method for Studies with a Categorical Factor 4.4 Correlation and Regression with a Measured Factor 4.4.1 What Type of Data Was Used to Record Your Factor and Outcome? 4.4.2 When Both the Factor and the Outcome Consist of Continuous Measured Values, Select Between Pearson and Spearman Correlation 4.5 Relevant Additional Material 5 Multiple Testing 5.1 What Is Multiple Testing and Why Does It Matter? 5.2 What Can We Do to Avoid an Excessive Risk of False Positives? 5.2.1 Use of Omnibus Tests 5.2.2 Distinguishing Between Primary and Secondary/ Exploratory Analyses 5.2.3 Bonferroni Correction 6 Common Issues and Pitfalls 6.1 Determining Equality of Standard Deviations 6.2 How Do I Know, in Advance, How Large My SD Will Be? 6.3 One‐Sided Versus Two‐Sided Testing 6.4 Pitfalls That Make Data Look More Meaningful Than It Really Is 6.4.1 Too Many Decimal Places 6.4.2 Percentages with Small Sample Sizes 6.5 Discussion of Statistically Significant Results 6.6 Discussion of Non‐Significant Results 6.7 Describing Effect Sizes with Non‐Parametric Tests 6.8 Confusing Association with a Cause and Effect Relationship 7 Contingency Chi‐Square Test 7.1 When Is the Test Appropriate? 7.2 An Example 7.3 Presenting the Data 7.3.1 Contingency Tables 7.3.2 Clustered or Stacked Bar Charts 7.4 Data Requirements 7.5 An Outline of the Test 7.6 Planning Sample Sizes 7.7 Carrying Out the Test 7.8 Special Issues 7.8.1 Yates Correction 7.8.2 Low Expected Frequencies — Fisher’s Exact Test 7.9 Describing the Effect Size 7.9.1 Absolute Risk Difference (ARD) 7.9.2 Number Needed to Treat (NNT) 7.9.3 Risk Ratio (RR) 7.9.4 Odds Ratio (OR) 7.9.5 Case: Control Studies 7.10 How to Report the Analysis 7.10.1 Methods 7.10.2 Results 7.10.3 Discussion 7.11 Confounding and Logistic Regression 7.11.1 Reporting the Detection of Confounding 7.12 Larger Tables 7.12.1 Collapsing Tables 7 12.2 Reducing Tables 7.13 Relevant Videos etc. 8 Independent Samples (Two‐Sample) T‐Test 8.1 When Is the Test Applied? 8.2 An Example 8.3 Presenting the Data 8.3.1 Numerically 8.3.2 Graphically 8.4 Data Requirements 8.4.1 Variables Required 8.4.2 Normal Distribution of the Outcome Variable Within the Two Samples 8.4.3 Equal Standard Deviations 8.4.4 Equal Sample Sizes 8.5 An Outline of the Test 8.6 Planning Sample Sizes 8.7 Carrying Out the Test 8.8 Describing the Effect Size 8.9 How to Describe the Test, the Statistical and Practical Significance of Your Findings in Your Report 8.9.1 Methods Section 8.9.2 Results Section 8.9.3 Discussion Section 8.10 Relevant Videos etc. 9 Mann–Whitney Test 9.1 When Is the Test Applied? 9.2 An Example 9.3 Presenting the Data 9.3.1 Numerically 9.3.2 Graphically 9.3.3 Divide the Outcomes into Low and High Ranges 9.4 Data Requirements 9.4.1 Variables Required 9.4.2 Normal Distributions and Equality of Standard Deviations 9.4.3 Equal Sample Sizes 9.5 An Outline of the Test 9.6 Statistical Significance 9.7 Planning Sample Sizes 9.8 Carrying Out the Test 9.9 Describing the Effect Size 9.10 How to Report the Test 9.10.1 Methods Section 9.10.2 Results Section 9.10.3 Discussion Section 9.11 Relevant Videos etc. 10 One‐Way Analysis of Variance (ANOVA) – Including Dunnett’s and Tukey’s Follow Up Tests 10.1 When Is the Test Applied? 10.2 An Example 10.3 Presenting the Data 10.3.1 Numerically 10.3.2 Graphically 10.4 Data Requirements 10.4.1 Variables Required 10.4.2 Normality of Distribution for the Outcome Variable Within the Three Samples 10.4.3 Standard Deviations 10.4.4 Sample Sizes 10.5 An Outline of the Test 10.6 Follow Up Tests 10.7 Planning Sample Sizes 10.8 Carrying Out the Test 10.9 Describing the Effect Size 10.10 How to Report the Test 10.10.1 Methods 10.10.2 Results Section 10.10.3 Discussion Section 10.11 Relevant Videos etc. 11 Kruskal–Wallis 11.1 When Is the Test Applied? 11.2 An Example 11.3 Presenting the Data 11.3.1 Numerically 11.3.2 Graphically 11.4 Data Requirements 11.4.1 Variables Required 11.4.2 Normal Distributions and Standard Deviations 11.4.3 Equal Sample Sizes 11.5 An Outline of the Test 11.6 Planning Sample Sizes 11.7 Carrying Out the Test 11.8 Describing the Effect Size 11.9 Determining Which Group Differs from Which Other 11.10 How to Report the Test 11.10.1 Methods Section 11.10.2 Results Section 11.10.3 Discussion Section 11.11 Relevant Videos etc. 12 McNemar’s Test 12.1 When Is the Test Applied? 12.2 An Example 12.3 Presenting the Data 12.4 Data Requirements 12.5 An Outline of the Test 12.6 Planning Sample Sizes 12.7 Carrying Out the Test 12.8 Describing the Effect Size 12.9 How to Report the Test 12.9.1 Methods Section 12.9.2 Results Section 12.9.3 Discussion Section 12.10 Relevant Videos etc. 13 Paired T‐Test 13.1 When Is the Test Applied? 13.2 An Example 13.3 Presenting the Data 13.3.1 Numerically 13.3.2 Graphically 13.4 Data Requirements 13.4.1 Variables Required 13.4.2 Normal Distribution of the Outcome Data 13.4.3 Equal Standard Deviations 13.4.4 Equal Sample Sizes 13.5 An Outline of the Test 13.6 Planning Sample Sizes 13.7 Carrying Out the Test 13.8 Describing the Effect Size 13.9 How to Report the Test 13.9.1 Methods Section 13.9.2 Results Section 13.9.3 Discussion Section 13.10 Relevant Videos etc. 14 Wilcoxon Signed Rank Test 14.1 When Is the Test Applied? 14.2 An Example 14.3 Presenting the Data 14.3.1 Numerically 14.3.2 Graphically 14.4 Data Requirements 14.4.1 Variables Required 14.4.2 Normal Distributions and Equal Standard Deviations 14.4.3 Equal Sample Sizes 14.5 An Outline of the Test 14.6 Planning Sample Sizes 14.7 Carrying Out the Test 14.8 Describing the Effect Size 14.9 How to Report the Test 14.9.1 Methods Section 14.9.2 Results Section 14.9.3 Discussion Section 14.10 Relevant Videos etc. 15 Repeated Measures Analysis of Variance 15.1 When Is the Test Applied? 15.2 An Example 15.3 Presenting the Data 15.3.1 Numerical Presentation of the Data 15.3.2 Graphical Presentation of the Data 15.4 Data Requirements 15.4.1 Variables Required 15.4.2 Normal Distribution of the Outcome Data 15.4.3 Equal Standard Deviations 15.4.4 Equal Sample Sizes 15.5 An Outline of the Test 15.6 Planning Sample Sizes 15.7 Carrying Out the Test 15.8 Describing the Effect Size 15.9 How to Report the Test 15.9.1 Methods Section 15.9.2 Results Section 15.9.3 Discussion Section 15.10 Relevant Videos etc. 16 Friedman Test 16.1 When Is the Test Applied? 16.2 An Example 16.3 Presenting the Data 16.3.1 Bar Charts of the Outcomes at Various Stages 16.3.2 Summarizing the Data via Medians or Means 16.3.3 Splitting the Data at Some Critical Point in the Scale 16.4 Data Requirements 16.4.1 Variables Required 16.4.2 Normal Distribution and Standard Deviations in the Outcome Data 16.4.3 Equal Sample Sizes 16.5 An Outline of the Test 16.6 Planning Sample Sizes 16.7 Follow Up Tests 16.8 Carrying Out the Tests 16.9 Describing the Effect Size 16.9.1 Median or Mean Values Among the Individual Changes 16.9.2 Split the Scale 16.10 How to Report the Test 16.10.1 Methods Section 16.10.2 Results Section 16.10.3 Discussion Section 16.11 Relevant Videos etc. 17 Pearson Correlation 17.1 Presenting the Data 17.2 Correlation Coefficient and Statistical Significance 17.3 Planning Sample Sizes 17.4 Effect Size and Practical Relevance 17.5 Regression 17.6 How to Report the Analysis 17.6.1 Methods 17.6.2 Results 17.6.3 Discussion 17.7 Relevant Videos etc. 18 Spearman Correlation 18.1 Presenting the Data 18.2 Testing for Evidence of Inappropriate Distributions 18.3 Rho and Statistical Significance 18.4 An Outline of the Significance Test 1 18.5 Planning Sample Sizes 18.6 Effect Size 18.7 Where Both Measures Are Ordinal 18.7.1 Educational Level and Willingness to Undertake Internet Research — An Example Where Both Measures Are Ordinal 18.7.2 Presenting the Data 18.7.3 Rho and Statistical Significance 18.7.4 Effect Size 18.8 How to Report Spearman Correlation Analyses 18.8.1 Methods 18.8.2 Results 18.8.3 Discussion 18.9 Relevant Videos etc. 19 Logistic Regression 19.1 Use of Logistic Regression with Categorical Outcomes 19.2 An Outline of the Significance Test 19.3 Planning Sample Sizes 19.4 Results of the Analysis 19.5 Describing the Effect Size 19.6 How to Report the Analysis 19.6.1 Methods 19.6.2 Results 19.6.3 Discussion 19.7 Relevant Videos etc. 20 Cronbach’s Alpha 20.1 Appropriate Situations for the Use of Cronbach’s Alpha 20.2 Inappropriate Uses of Alpha 20.3 Interpretation 20.4 Reverse Scoring 20.5 An Example 20.6 Performing and Interpreting the Analysis 20.7 How to Report Cronbach’s Alpha Analyses 20.7.1 Methods Section 20.7.2 Results 20.7.3 Discussion 20.7 Relevant Videos etc. mySku 4743

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