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Activity Number: 194
Type: Contributed
Date/Time: Monday, August 5, 2013 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #309420
Title: An Assessment of the Impact of Missing Values on Statistical Methods for Binary Repeated Measures and Hierarchical Data
Author(s): Elmabrok Masaoud*+ and Henrik Stryhn
Companies: and University of Prince Edward Island
Keywords: Simulation ; Missing values ; Repeated Measures data ; Binary data
Abstract:

A simulation study was targeted at data on high somatic cell counts (SCC) in milk samples of dairy cattle. Missing values were simulated from a variant of Diggle's (1994) logistic random effects model. Three types of missing values corresponded to missingness patterns present in a real SCC dataset were simulated: delayed entry, drop-outs and intermittent missing values.

Results showed that ALR, PQL, ML and MCMC estimation procedures performed well and produced estimates with small relative bias.


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