Applied Missing Data Analysis in the Health Sciences

List of Tables

1. 1.1 Regression Results Under Different Missing Data Mechanisms, Using Full Data, Data with Completely Observed Values, and Data with Missing Values, Respectively
2. 1.2 Missing Data Pattern for SCL-20 Scores Over Time
3. 4.1 Linear Regression with Y₂ as Outcome
4. 4.2 Linear Regression with Y₂ as Covariate
5. 4.3 Cross-Sectional Analysis Result for the IMPACT study
6. 4.4 Cross-Sectional Analysis Result for the NACC Study
7. 4.5 Bayesian Analysis Results for the NHANES Example
8. 4.6 Regression Analysis for the Cross-Sectional Simulated Data Based on Imputation Methods
9. 4.7 The Estimated Location and Scale Parameters with the Associated Standard Errors for the NACC Data
10. 5.1 The Missing Data Pattern in the SCL-20 Scores at Baseline, 3, 6, 12, 18, and 24 Months
11. 5.2 Missing Data Pattern for the UDS Data
12. 5.3 Common Choices of Working Correlation R_i with the Cluster Size n_i = 4
13. 5.4 Percentages of Missingness by Treatment and Month
14. 5.5 Estimates Based on the Complete-Case Analysis
15. 5.6 Estimates Based on the Available Data Analysis
16. 5.7 Estimates Based on the LOCF Analysis
17. 5.8 The Average of Estimated Regression Parameters for the Full Data Estimator, Available Case Analysis (GEE), IPWGEE1, and IPWGEE
18. 5.9 Estimates Based on the IPWGEE1 Analysis
19. 5.10 Estimates Based on the IPWGEE2 Analysis
20. 5.11 Analysis Results of NACC UDS Data
21. 5.12 Estimates Based on the Multiple Imputation with Monotone Missingness
22. 5.13 Estimates Based on the Multiple Imputation with Multivariate Normal Distribution
23. 5.14 ...