期刊
JOURNAL OF APPLIED STATISTICS
卷 45, 期 5, 页码 918-931出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/02664763.2017.1322558
关键词
Higher education participation; measurement errors; misclassification errors; MCMC; missing data; multilevel
资金
- Economic and Social Research Council [ES/K007246/1] Funding Source: researchfish
- ESRC [ES/K007246/1] Funding Source: UKRI
In this paper we consider the impact of both missing data and measurement errors on a longitudinal analysis of participation in higher education in Australia. We develop a general method for handling both discrete and continuous measurement errors that also allows for the incorporation of missing values and random effects in both binary and continuous response multilevel models. Measurement errors are allowed to be mutually dependent and their distribution may depend on further covariates. We show that our methodology works via two simple simulation studies. We then consider the impact of our measurement error assumptions on the analysis of the real data set.
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