1. Missing Data Handling: Thinking It Through
James Peugh, Ph. D.
Cincinnati Children’s Hospital
Medical Center

2. Overview & Outline
Examine Missing Data Handling in Four SEM-Based Analyses
Categorical CFA with Covariate (MIMIC Model)
Moderated Mediation (MacArthur Method)
SEM with a Latent Variable Interaction Term
Multilevel ANCOVA SEM
Keep Two Questions in Mind:
What are your options for missing data handling?: ML & MI
What does MAR mean, and how can I make that more plausible in my analysis model?

3. Categorical Indicator CFA with Covariate (HA: Imputation) (Folder Model_1.zip)

4. HB_ss
Sickle-Cell Disease Responsibility
Scale Measured by 17 Items Assessed on a 1-3 Categorical Scale (10% - 20% Missing Data at the Item Level)
HB_ss = Hemoglobin Type SS
*Also have Gender, Age, and Pediatrics-QL Subscale Scores

5. HA: (Saturated) Model Imputation
Multiple Imputation is a Model
HA: Imputation, or Saturated Model
Is a Model with 0 df
Essentially imputes based on a correlation matrix
Specifies all possible relationships among both analysis and auxiliary variables
Why auxiliary variables in addition to analysis variables?
MAR: Says missing on your analysis variables are related to variables included in your analysis model
*Auxiliary: Adding extra information, but without biasing results

6. HA: Imputation Analysis
Key Points for Analyzing Imputed Data
Check the .OUT file from imputation for the order of the variables in the imputed datasets
Mplus input for analysis of imputed data is a list file generated by imputation

7. Mplus pools imputed analysis results
Extra material: Scale reliability (α = 0.967)

8. Moderated Mediation-Mac Arthur Method (Folder Model_2.zip)

9. Moderated Mediation: MacArthur
Definitions:
Z Moderates an X→Y relationship if the relationship is significant conditional on values of Z
M Mediates an X→Y relationship if M explains how/why X relates to Y
Temporal Order Requirements:
Z is a Moderator ONLY if it Precedes X
M is a Mediator ONLY if X Precedes M
Moderation Requirements:
The M*X interaction, “must always be included in the linear model” (Kraemer, et al., p.1680)
Why?
Kraemer, et al. (2008)
VanderWeele (2015)

11. Perceived Media Influence: Tal-Or, et al., 2010
Reaction (Y): How willing consumers would be to buy a good/service based on a media story
Import(ant) (M): How important a perceived shortage in a good/service would be in a decision to buy
Cond(ition) (X): 0 for a less visible media story, 1 for a more visible story
PMI (Z): How inclined you believe others would be to buy based on perceived media influence
MZ: Importance * PMI interaction

12. The Mplus Syntax

14. SEM Latent Variable Moderator (HA: Imputation) (Folder Model_3.zip)

15. Why HA: Imputation?

16. Mplus

17. Multilevel ANCOVA (H0: Imputation) (Folder Model_4.zip)

18. Why H0: Imputation? WITHIN or LEVEL 1 (Students)
BETWEEN or LEVEL 2 (Classes)
Why H0: Imputation?

19. Mplus