References
- W.J. Browne, H. Goldstein, G. Woodhouse, and M. Yang, An MCMC algorithm for adjusting for errors in variables in random slopes multilevel models, Multilevel Model. Newslett. 13 (2001), pp. 4–9.
- J.P. Buonaccorsi, Measurement Error: Models, Methods and Applications, Chapman and Hall–CRC Press, Boca Raton, 2010, xxvi + 438 pp. ISBN 978-1-420-06656-0.
- J.R. Carpenter and M.G. Kenward, Multiple Imputation and its Application, Wiley, Chichester, 2013.
- R.J. Carroll, D. Ruppert, L.A. Stefanski, and C. Crainiceanu, Measurement Error in Nonlinear Models: A Modern Perspective, Chapman & Hall, Boka Raton, FL, 2006.
- C.M.J. Charlton, D.T. Michaelides, R.M.A. Parker, B. Cameron, C. Szmaragd, H. Yang, Z. Zhang, A.J. Frazer, H. Goldstein, K. Jones, G. Leckie, L. Moreau, and W.J. Browne, Stat-JR Version 1.0, Centre for Multilevel Modelling, University of Bristol & Electronics and Computer Science, University of Southampton, 2013.
- D. Clayton, Models for the analysis of cohort and case-control studies with inaccurately measured exposures, in Statistical Models for Longitudinal Studies on Health, J.H. Dwyer, M. Feinlieb, P. Lippert, and H. Hoffmeister, eds., Oxford University Press, Oxford, 1992, pp. 301–331.
- J. Cumming and H. Goldstein, Handling attrition and non-response in longitudinal data with an application to a study of Australian youth, Longit. Lifecourse Stud. J. 7 (2016), pp. 53–63. doi:doi: 10.14301/llcs.v7i1.342.
- R. Ecob and H. Goldstein, Instrumental variable methods for the estimation of test score reliability, J. Educ. Statist. 8 (1983), pp. 223–241. doi: 10.2307/1164761
- L. Feinstein, J. Jerrim, A. Vignoles, H. Goldstein, R. French, E. Washbrook, R. Lee, and R. Lupton, Comment and debate: Social class differences in early cognitive development, Longit. Life Course Stud. 6 (2015). doi:doi: 10.14301/llcs.v6i3.361.
- W.A. Fuller, Measurement Error Models, Wiley, New York, 1987.
- H. Goldstein, Some models for analysing longitudinal data on educational attainment (with discussions), J. Roy. Statist. Soc. Ser. A 142 (1979), pp. 407–442. doi: 10.2307/2982551
- H. Goldstein, J.R. Carpenter, and W.J. Browne, Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms, J. Roy. Statist. Soc. Ser. A 177 (2014), pp. 553–564. doi:doi: 10.1111/rssa.12022.
- H. Goldstein, J. Carpenter, M. Kenward, and K. Levin, Multilevel models with multivariate mixed response types, Statist. Model. 9 (2009), pp. 173–197. doi: 10.1177/1471082X0800900301
- H. Goldstein and D. Kounali, Multilevel multivariate modelling of childhood growth, numbers of growth measurements and adult characteristics, J. R. Statist. Soc. A 172(Part 3) (2009), pp. 599–613. doi: 10.1111/j.1467-985X.2008.00576.x
- H. Goldstein, D. Kounali, and A. Robinson, Modelling measurement errors and category misclassifications in multilevel models, Statist. Model. 8 (2008), pp. 243–261. doi: 10.1177/1471082X0800800302
- MATLAB and Statistics Toolbox Release, The MathWorks, Inc., Natick, Massachusetts, United States, 2007b.
- S. Muff and L.F. Keller, Reverse attenuation in interaction terms due to covariate measurement error, Biom. J. 57 (2015), pp. 1068–1083. doi:doi: 10.1002/bimj.201400157.
- S. Muff, A. Riebler, L. Held, H. Rue, and P. Saner, Bayesian analysis of measurement error models using integrated nested Laplace approximations, Appl. Statist. 64 (2015), pp. 231–252.
- H. Goldstein, Multilevel Statistical Models, Wiley, Chichester, 2011.
- S. Richardson and W.R. Gilks, Conditional independence models for epidemiological studies with covariate measurement error, Stat. Med. 12 (1993), pp. 1703–1722. doi: 10.1002/sim.4780121806
- D.B. Rubin, Multiple Imputation for Non Response in Surveys, Wiley, Chichester, 1987.
- A. Skrondal and S. Rabe-Hesketh, Generalized Latent Variable Modelling: Multilevel, Longitudinal and Structural Equation Models, Chapman and Hall/CRC, Boca Raton, FL, 2004.