Warehouse Stock Clearance Sale

Grab a bargain today!


Statistics for Dental Clinicians
By

Rating

Product Description
Product Details

Table of Contents

Preamble xi

1 What is statistics and why do we need it? 1

Selected readings 7

2 Understanding and interpreting measures of association 8

Effect and effect size 8

Dichotomous outcome variables 9

Data presentation and interpretation 9

Absolute risk 9

Absolute risk difference 10

Relative risk or risk ratio 10

Odds ratio 11

Mean difference 11

A few additional notes 12

Selected readings 16

3 Understanding and interpreting a standard deviation and normal distribution 17

A few additional notes 22

Selected readings 23

4 Understanding and interpreting standard error 24

Interpretation of the standard error of the mean 25

Implication of the standard error of the mean 26

A few additional notes 26

Selected readings 29

5 Understanding and interpreting hypothesis testing and p-values 30

Descriptive and inferential statistics 30

Sampling error 31

Hypothesis testing or null hypothesis significance testing 31

Null and alternative hypotheses 32

Significance 33

P-value 34

A few additional notes 36

Selected readings 37

6 Understanding and interpreting a confidence interval 38

Understanding the confidence interval 39

How to interpret a confidence interval 39

A few additional notes 41

Selected readings 44

7 Understanding and interpreting power analysis and sample size 45

Sample size: Why is it important? 45

Components of a sample size calculation 46

Size of the effect 46

Significance level and type I error 47

Power and type II error 49

A few additional notes 50

Selected readings 53

8 Understanding and interpreting a survival analysis 54

Kaplan-Meier or survival curve 55

Comparing two Kaplan-Meier (survival) curves 57

Cox proportional hazard model 58

A few additional notes 59

Selected readings 60

9 Understanding and interpreting a probabilistic-based diagnosis 61

Sensitivity 61

Specificity 63

Positive predictive value 63

Negative predictive value 63

Likelihood ratios 65

Selective readings 68

10 Understanding and interpreting a correlation 69

Pearson product-moment correlation 69

Interpretation of Pearson correlation coefficients and coefficient of determination 71

Misinterpretation of correlations 73

A few additional notes 74

Selected readings 74

11 Understanding and interpreting a regression analysis 76

Estimation 76

Prediction 77

Linear regression 77

Multiple (or multivariable) linear (MLR) regression 79

Logistic regression 79

Predicting risk and odds 80

A hypothetical example: predicting risk and odds of an outcome 80

Estimating odds ratios 81

A hypothetical example--estimating an odds ratio 81

Nonindependence of observations 82

Building a regression model 82

A few additional notes 82

Selected readings 85

12 Understanding and interpreting confounding and effect modification 86

Counterfactual framework and causal reasoning 86

Causal inference and confounding bias 87

Strategies to deal with confounding in the study design phase 89

1. Randomization 90

2. Specification 90

3. Matching 90

Strategies to deal with confounding in the analysis phase 92

1. Stratification 92

2. Propensity score 92

3. Traditional regression modeling 93

Effect modification 94

A few additional notes 95

Selected readings 97

13 Understanding and interpreting bias 98

Random error versus systematic error (bias) 98

What does it really mean? 99

Distinguishing risk of bias, methodological quality, and reporting quality 100

Assessing risk of bias in primary studies 101

A few additional notes 104

Selected readings 105

14 Understanding and interpreting patient-reported outcomes 106

Identifying optimal patient-reported outcome measures 108

Validity 108

Reliability 109

A hypothetical scenario--Cohen's kappa (k) 109

Responsiveness 110

A few additional notes 111

Selected readings 112

15 Understanding and interpreting a cross-sectional study 113

Bias in cross-sectional studies 113

Response rate and avoiding nonresponse 114

Analysis of cross-sectional studies 115

Advantages and limitations of a cross-sectional study 116

A few additional notes 116

Selected readings 119

16 Understanding and interpreting a case-control study 120

Selection of the study population 120

Identifying cases 120

Identifying controls 122

Retrospective assessment of the exposure 122

Strengths and limitations 124

Selected readings 125

17 Understanding and interpreting a cohort study 126

Types of cohort study designs 126

Selection of the study population 127

Measuring exposures 128

Measuring outcome frequency 129

Measures of association 129

Bias in cohort studies 130

Selection bias 130

Nonparticipation and nonresponse 130

Loss to follow-up or attrition bias 130

Information bias: Dissimilar information between exposed and unexposed participants 130

Confounding 131

Strengths and limitations 131

Suggested readings 132

18 Understanding and interpreting a randomized controlled trial 133

Study arms 135

Type of outcomes 135

Methodological strategies in randomized controlled trials 137

Nonadherence to study protocol 137

Missing data 139

Subgroup analysis or effect modification 140

A few additional notes 142

Selected readings 144

19 Understanding and interpreting meta-analyses 145

The value of meta-analysis 145

Pairwise meta-analysis 146

Fixed effect meta-analysis 146

Random effects meta-analysis 147

Weight of each study in a meta-analysis 147

Forest plots 147

Heterogeneity 149

Network meta-analysis 151

Sensitivity analysis 152

Certainty of the evidence 152

A few additional notes 153

Selected readings 154

20 Understanding and interpreting statistical and clinical significance 155

A few additional notes 158

Selected readings 158

Appendix 1 Formulas and equations 160

Appendix 2 Z-table 183

Appendix 3 T-table 185

Glossary 189

Index 210

About the Author

Michael Glick, DMD, FDS RCSEd, is Professor of Oral Medicine and Executive Director, Center for Integrative Global Oral Health in the School of Dental Medicine at the University of Pennsylvania in Philadelphia, Pennsylvania, USA.

Alonso Carrasco-Labra, DDS, MSc, PhD, is an Associate Professor in the Department of Preventive & Restorative Sciences and Director, Cochrane Oral Health Collaborating Center at Penn Dental Medicine, Center for Integrative Global Oral Health in the School of Dental Medicine at the University of Pennsylvania in Philadelphia, Pennsylvania, USA.

Olivia Urquhart, MPH, is an Instructor in the Department of Preventive & Restorative Sciences, Center for Integrative Global Oral Health in the School of Dental Medicine at the University of Pennsylvania in Philadelphia, Pennsylvania, USA.

Ask a Question About this Product More...
 
Look for similar items by category
This title is unavailable for purchase as none of our regular suppliers have stock available. If you are the publisher, author or distributor for this item, please visit this link.

Back to top
We use essential and some optional cookies to provide you the best shopping experience. Visit our cookies policy page for more information.