Tables and Figures

Tables

  1. 4.1 Impact of Alternative Resource Measures on Poverty Rates
  2. 4.2 Distribution of the Poor by the Amount of Their Unmet Needs (1994)
  3. 5.1 Impact of Shifts in the Distribution of Health on Selected Measures of Inequality
  4. 5.2 Calculation of Group-Based Ranking in the Cumulative Distribution of Education
  5. 5.3 Total, Within- and Between-Group Inequality in Body Mass Index by Education and Gender
  6. 5.4 Means and Regression Coefficients for Weight (kg) for Covariates
  7. 5.5 Components of the Mean Difference in Weight (kg) for Blacks and Whites
  8. 5.6 Determinants of Socioeconomic Inequality in Physical Activity Among Men in the Americas Region
  9. 5A.1 Common Inequality Measures Based on Disproportionality Functions
  10. 6.1 Properties of Segregation Measures
  11. 8.1 Principles of Community-Based Participatory Research
  12. 9.1 Four Classic SNA Studies
  13. 9.2 Glossary of SNA Concepts
  14. 9.3 Adjacency Matrix Corresponding to Figure 9.1
  15. 11.1 Anova Partition of the Sums of Squares in a Single Cross-Section Group Randomized Trial Having Unit as a Random Effect
  16. 11.2 Anova Table for the Repeated Measures Analysis in a Nested Cohort Design or the Pre/Post-Test Analysis in a Nested Cross-Section Design
  17. 11.3 Impact on the Factor (t1−a/2 + tpower) in Power Calculations as a Function of df Available
  18. 12.1 Covariate Imbalance Across Exposure Groups Prior to Matching
  19. 12.2 Reduction in Covariate Imbalance after Matching on the Propensity Score
  20. 13.1 Prevalence of Heavy Episodic Drinking by Wave in the Analyzed Subsample of the National Longitudinal Study of Adolescent Health
  21. 13.2 Baseline Predictors and Time-Varying Marijuana Use across Adolescence to Adulthood in Predicting the Intercept and Slope of Log Odds of Heavy Episodic Drinking
  22. 13.3 Respondent Childhood and Adult Characteristics by Adult Neighborhood Disadvantage, African American Respondents, in the Panel Study on Income Dynamics (PSID), 1999 (n = 251)
  23. 14.1 Difference-in-Differences in Potential Outcomes
  24. 14.2 Difference-in-Differences in Regression Coefficients
  25. 15.1 Fixed Effects, Random Effects, and Hybrid Fixed Effects: Linear Model Equations and STATA/SAS Code for Linear and Logistic Models
  26. 15.2 Multilevel Example Results: Black–White PTB Disparity Within and Between Neighborhoods
  27. 17.1 Illustration of Parametric Substitution Estimator Implementation for the CRD and CPAR of the Relation Between Physical Abuse and Psychopathology

Figures

  1. 1.1 Conceptual Framework for Multilevel Thinking
  2. 2.1 Fundamental Graph of Public Health
  3. 4.1 Census Poverty Rate by Age—1966 to 2012
  4. 5.1 Average Body Mass Index and Kernal Density Estimates by Years of Completed Education for Women Aged 25 to 64
  5. 5.2 Proportion of Individuals under Age 65 with Health Insurance, 1998–2009, by Race-Ethnicity
  6. 5.3 Percentage of Stunted Children for Poorest and Richest Wealth Quantiles, Selected Countries
  7. 5.4 Diverging Scenarios for Absolute and Relative Inequality Trends
  8. 5.5 Hypothetical Life Expectancy for Three Social Groups with Varying Population Sizes in Two Different Societies
  9. 5.6 Graphical Example of a Lorenz Curve for Health
  10. 5.7 Relative and Absolute Health Concentration Curves for Daily Smoking in Brazil and Dominican Republic, 2002
  11. 5.8 Income-Based Slope and Relative Index of Inequality in Current Smoking
  12. 5.9 Graphical Depiction of Blinder–Oaxaca Decomposition
  13. 6.1 The Checkerboard Problem
  14. 6.2 The Modifiable Areal Unit Problem
  15. 7.1 Cluster Map from Concept Mapping of Urban Neighborhood Factors and Intimate Partner Violence
  16. 7.2 Neighborhood Stabilization Factors and IPV Cessation. Diagram of the Relationship Between Items Drawn by Participants
  17. 7.3 Neighborhood Monitoring Cluster and IPV
  18. 9.1 Example 7-Node Network
  19. 9.2 Selection and Influence Processes
  20. 11.1 Variance of a Unit Mean as a Fraction of Within-Unit Variance, σ2, Plotted Against the Number of Members per Unit, at Different Levels of the Cluster Effect, VCR
  21. 11.2 Relationship Between the Detectable Difference (Δ) and Power
  22. 12.1 Conceptual Diagram of Target Values and Causal Contrast
  23. 12.2 Fictitious Graph of Overlap in Propensity Scores
  24. 12.3 Overlap in Propensity Scores by the Neighborhood Exposure Group
  25. 12.4 Effect Estimates as a Function of Caliper Width
  26. 13.1 Growth Model for Heavy Episodic Drinking from Adolescence to Adulthood in a Subsample of the National Longitudinal Study of Adolescent Health
  27. 13.2 Hypothetical Disease Prevalence Across Age in a Cross-Sectional Study
  28. 13.3 Hypothetical Disease Prevalence by Age and Time Period
  29. 13.4 Hypothetical Disease Prevalence by Time Period and Birth Cohort
  30. 13.5 Period and Cohort Effects on Asthma Prevalence in the United States 1997–2011 Using a Cross-Classified Random Effects Model
  31. 13.6 Time-Dependent Confounding
  32. 13.7 Time-Dependent Confounding with Common Cause of L and Y
  33. 13.8 Conditioning on Baseline Outcome Status
  34. 13.9 Differential Loss to Follow-up
  35. 13.10 Histograms Denoting the Distribution of Stabilized Inverse Probability of Treatment Weights by Level of Neighborhood Disadvantage
  36. 14.1 Graphical Example of DD Estimate
  37. 15.1 Between- and Within-Cluster Variation and Potential for Cluster-Level Confounding
  38. 15.2 Decision Tree for Random Effects, Fixed Effects, or Hybrid Model Selection
  39. 16.1 Mediation Model in Baron and Kenny (1986)
  40. 16.2 Causal Diagrams Showing Conditions Needed to Identify Total Effects, Controlled Direct Effects, and Natural Direct and Indirect Effects
  41. 16.3 Causal Diagram of the Effects of a Hypothetical Conditional Cash Transfer Program on Children's Height-for-Age
  42. 16.4 Causal Diagram Showing the Mediation Model with Two Mediators of Interest
  43. 16.5 Causal Diagram Showing Unmeasured Confounding of the Meadiator-Outcome Relation by the Confounder U
  44. 16.6 Causal Diagram Illustrating a Non-Differential Error in the Measurement of the Mediator
  45. 17.1 Directed Acyclic Graph or DAG of the Causal Relations Between the Exposure A, Outcome Y, and Confounding Variable W
  46. 18.1 Definitions of Terminology Applied to an Example Causal DAG, with Corresponding Causal Assumptions and Implied Independencies
  47. 18.2 A DAG to Illustrate Identification of Paths Connecting Variables and Covariates That Block Paths
  48. 18.3 A DAG under Which Conventional Confounding Rules Fail
  49. 18.4 A DAG for Selection Bias
  50. 18.5 An Example Illustrating Inclusion of a Measurement Error in Exposure and Outcome, with the Outcome Measurement Error Influenced by the Value of the Exposure
  51. 19.1 Causal Diagrams Depicting a Valid Instrument
  52. 19.2 Causal Diagrams Depicting Variables That Are Not Valid Instruments
  53. 19.3 Characterization of Individuals Based on How the Instrumental Variable or Random Assignment Affects the Exposure or Treatment Variable
  54. 19.4 Example Contrasting ITT, IV, and Population Average Causal Effect in Two Populations
  55. 19.5 Sample Size Required to Achieve 80% Power at α = 0.05 with Improvements in the First-Stage Association