Conference Program day 1: Tuesday April 9
|09:30||Keynote 1: Todd Little
On the Merits of Longitudinal Multiple-Group Fixed Effects Modeling Versus Multilevel Modeling for Evaluating Interventions.
(Not) Everybody Does: Testing for Individual Differences and Similarities in Hierarchical data.
Income Equality in Achievement among US Elementary Schools: A Random Coefficients Model with Data MAR.
|10:40||Coffee and Tea Break|
How to Compare Data from Very Different Sources: A 4-level Longitudinal Model of Institutional Trust.
Sample size formulas for cluster randomized repeated measurement designs with p>2 levels.
Optimal developmental trajectory group analyses: Which parameters should (not) be constrained to accurately estimate growth mixture models?
A joint modelling approach to relate within-individual variability in a repeatedly measured exposure to a future outcome, allowing for measurement error in the repeated measures.
|12:20||Lunch – Poster session|
Multilevel Propensity Scores: An Evaluation of Findings.
Calculating intraclass correlation coefficients in multilevel models for count responses.
On the use of pairwise maximum likelihood estimation for clustered data.
Why country dummies sometimes do not do the job. How to get the within-estimator of cross-level interactions with pooled cross-sections.
Multiple imputation and selection of ordinal level-2 predictors in multilevel models: analysis of the relationship between student ratings and teacher beliefs and practices.
Missing data imputation in large combined cross-sectional and longitudinal data: multilevel multiple imputation and time series imputation.
|15:30||Coffee and Tea Break|
Multiple Imputation in Three-level Models.
Multiple imputation of missing data in multilevel models with random slopes and nonlinear effects.
|16:30||Keynote 2: Stef van Buuren
Recipes for multilevel imputation.
|17:00||End of day 1|
|17:00||Drinks and conference dinner (for those who registered)|