Goldstein, H;
Browne, WJ;
Charlton, C;
(2018)
A Bayesian model for measurement and misclassification errors alongside missing data, with an application to higher education participation in Australia.
Journal of Applied Statistics
, 45
(5)
pp. 918-931.
10.1080/02664763.2017.1322558.
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Abstract
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.
| Type: | Article |
|---|---|
| Title: | A Bayesian model for measurement and misclassification errors alongside missing data, with an application to higher education participation in Australia |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/02664763.2017.1322558 |
| Publisher version: | https://doi.org/10.1080/02664763.2017.1322558 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Higher education participation, measurement errors, misclassification errors, MCMC, missing data, multilevel |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10058814 |
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