Comparison of methods for imputing limited-range variables: a simulation study

被引：0

作者：

Laura Rodwell

Katherine J Lee

Helena Romaniuk

John B Carlin

机构：

[1] Clinical Epidemiology and Biostatistics Unit,Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences

[2] Murdoch Childrens Research Institute,Centre for Adolescent Health

[3] The University of Melbourne,undefined

[4] Murdoch Childrens Research Institute,undefined

来源：

BMC Medical Research Methodology | / 14卷

关键词：

Multiple imputation; Limited-range; Skewed data; Missing data; Rounding; Truncated regression;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

共 62 条

[1]

Little RJ(2012)The prevention and treatment of missing data in clinical trials N Engl J Med 367 1355-1360

[2]

D’Agostino R(2012)Missing Data New Engl J Med 367 1353-1354

[3]

Cohen ML(1996)Multiple Imputation after 18+ Years J Am Stat Assoc 91 473-489

[4]

Dickersin K(2002)Missing data: Our view of the state of the art Psychol Methods 7 147-177

[5]

Emerson SS(2007)Multiple imputation of discrete and continuous data by fully conditional specification Stat Methods Med Res 16 219-242

[6]

Farrar JT(2010)A Simple Method to Ensure Plausible Multiple Imputation for Continuous Multivariate Data Commun Stat Simulat 39 1779-1784

[7]

Frangakis C(2001)A multivariate technique for multiply imputing missing values using a sequence of regression models Surv Methodol 27 85-95

[8]

Hogan JW(2010)Missing data analysis using multiple imputation: getting to the heart of the matter Circ Cardiovasc Qual Outcomes 3 98-105

[9]

Molenberghs G(2005)Multiple imputation for missing ordinal data J Mod App Stat 4 26-632

[10]

Murphy SA(2010)Multiple Imputation for Missing Data: Fully Conditional Specification Versus Multivariate Normal Imputation Am J Epidemiol 171 624-138