ICPS
2019 International Convention of Psychological Science · 2019
A Comparison of Missing Data Methods for Single-Case Randomization Tests
- Tamal Kumar De
KU Leuven - René Tanious
KU Leuven - Bart Michiels
KU Leuven - Patrick Onghena
KU Leuven
Abstract
Analysis of single-case experiments is often hindered by the presence of missing data. In this poster, we present results from a simulation study comparing three missing data handling methods for single-case experiments in terms of Type I error rate and estimated power in a randomization test.
Statistics and Methodology
