Longitudinal multiple imputation approaches for body mass index or other variables with very low individual-level variability: the mibmi command in Stata

[1]  Evangelos Kontopantelis,et al.  Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis , 2015, BMJ : British Medical Journal.

[2]  Evangelos Kontopantelis,et al.  Glucose, blood pressure and cholesterol levels and their relationships to clinical outcomes in type 2 diabetes: a retrospective cohort study , 2015, Diabetologia.

[3]  Ian R White,et al.  Evaluation of two-fold fully conditional specification multiple imputation for longitudinal electronic health record data , 2014, Statistics in medicine.

[4]  Irene Petersen,et al.  Application of Multiple Imputation using the Two-Fold Fully Conditional Specification Algorithm in Longitudinal Clinical Data , 2014, The Stata journal.

[5]  I. White,et al.  Two‐stage method to remove population‐ and individual‐level outliers from longitudinal data in a primary care database , 2012, Pharmacoepidemiology and drug safety.

[6]  John B Carlin,et al.  Recovery of information from multiple imputation: a simulation study , 2012, Emerging Themes in Epidemiology.

[7]  A Rogier T Donders,et al.  Dealing with missing outcome data in randomized trials and observational studies. , 2012, American journal of epidemiology.

[8]  Jaakko Nevalainen,et al.  Missing values in longitudinal dietary data: A multiple imputation approach based on a fully conditional specification , 2009, Statistics in medicine.

[9]  S. Silverman,et al.  From randomized controlled trials to observational studies. , 2009, The American journal of medicine.

[10]  C. Saha,et al.  Bias in the last observation carried forward method under informative dropout , 2009 .

[11]  M. Kenward,et al.  A comparison of multiple imputation and doubly robust estimation for analyses with missing data , 2006 .

[12]  Vic Hasselblad,et al.  Can one assess whether missing data are missing at random in medical studies? , 2006, Statistical methods in medical research.

[13]  Jürgen Unützer,et al.  A comparison of imputation methods in a longitudinal randomized clinical trial , 2005, Statistics in medicine.

[14]  Paula Diehr,et al.  Imputation of missing longitudinal data: a comparison of methods. , 2003, Journal of clinical epidemiology.

[15]  J. Schafer,et al.  Missing data: our view of the state of the art. , 2002, Psychological methods.

[16]  D. Rubin.  Multiple Imputation After 18+ Years , 1996 .