Evaluation of approaches for multiple imputation of three-level data

[1] Yucel RM(2011)Random covariances and mixed-effects models for imputing multivariate multilevel continuous data Stat Model 11 351-370

[2] Mundy LK(2013)Study protocol: the childhood to adolescence transition study (CATS) BMC Pediatr 13 160-713

[3] Simmons JG(2015)The rise of multiple imputation: a review of the reporting and implementation of the method in medical research BMC Med Res Methodol 15 30-487

[4] Allen NB(2018)A comparison of multilevel imputation schemes for random coefficient models: fully conditional specification and joint model imputation with random covariance matrices Multivar Behav Res 53 695-1865

[5] Viner RM(2015)Multiple imputation of covariates by fully conditional specification: accommodating the substantive model Stat Methods Med Res 24 462-96

[6] Bayer JK(2016)Multilevel multiple imputation: a review and evaluation of joint modeling and chained equations imputation Psychol Methods 21 222-1064

[7] Olds T(2011)Missing data techniques for multilevel data: implications of model misspecification J Appl Stat 38 1845-568

[8] Williams J(2017)Multiple imputation of missing data in multilevel designs: a comparison of different strategies Psychol Methods 22 141-95

[9] Olsson C(2001)A multivariate technique for multiply imputing missing values using a sequence of regression models Surv Methodol 27 85-431

[10] Romaniuk H(2006)Fully conditional specification in multivariate imputation J Stat Comput Simul 76 1049-457

[1] Yucel RM(2011)Random covariances and mixed-effects models for imputing multivariate multilevel continuous data Stat Model 11 351-370

[2] Mundy LK(2013)Study protocol: the childhood to adolescence transition study (CATS) BMC Pediatr 13 160-713

[3] Simmons JG(2015)The rise of multiple imputation: a review of the reporting and implementation of the method in medical research BMC Med Res Methodol 15 30-487

[4] Allen NB(2018)A comparison of multilevel imputation schemes for random coefficient models: fully conditional specification and joint model imputation with random covariance matrices Multivar Behav Res 53 695-1865

[5] Viner RM(2015)Multiple imputation of covariates by fully conditional specification: accommodating the substantive model Stat Methods Med Res 24 462-96

[6] Bayer JK(2016)Multilevel multiple imputation: a review and evaluation of joint modeling and chained equations imputation Psychol Methods 21 222-1064

[7] Olds T(2011)Missing data techniques for multilevel data: implications of model misspecification J Appl Stat 38 1845-568

[8] Williams J(2017)Multiple imputation of missing data in multilevel designs: a comparison of different strategies Psychol Methods 22 141-95

[9] Olsson C(2001)A multivariate technique for multiply imputing missing values using a sequence of regression models Surv Methodol 27 85-431

[10] Romaniuk H(2006)Fully conditional specification in multivariate imputation J Stat Comput Simul 76 1049-457