Multiple Imputation When Rate of Change is the Outcome of Interest

被引：0
|
作者：
Desai, Manisha [1 ]
Mitani, Aya A. [2 ]
Bryson, Susan W. [3 ]
Robinson, Thomas [3 ,4 ]
机构：
[1] Stanford Univ, Dept Med, Biomed Informat Res, Stanford, CA 94305 USA
[2] Boston Univ, Dept Biostat, Boston, MA 02215 USA
[3] Stanford Univ, Dept Pediat, Stanford, CA 94305 USA
[4] Stanford Univ, Dept Med, Stanford, CA 94305 USA
来源：
JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2016年 / 15卷 / 01期
关键词：
Multiple imputation; derived variables; active imputation; passive imputation; mixed effects model; two-stage linear regression; slope;
D O I：
暂无
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
Little research has been devoted to multiple imputation (MI) of derived variables. This study investigates various MI approaches for the outcome, rate of change, when the analysis model is a two-stage linear regression. Simulations showed that competitive approaches depended on the missing data mechanism and presence of auxiliary terms.
引用
收藏
页码：160 / 192
页数：33
相关论文
共 50 条
  • [1] Multiple imputation models should incorporate the outcome in the model of interest
    Bartlett, Jonathan W.
    Frost, Chris
    Carpenter, James R.
    [J]. BRAIN, 2011, 134
  • [2] Reply: Multiple imputation models should incorporate the outcome in the model of interest
    Weigand, Stephen D.
    Jack, Clifford R., Jr.
    [J]. BRAIN, 2011, 134
  • [3] Multiple imputation for handling missing outcome data when estimating the relative risk
    Thomas R. Sullivan
    Katherine J. Lee
    Philip Ryan
    Amy B. Salter
    [J]. BMC Medical Research Methodology, 17
  • [4] Multiple imputation for handling missing outcome data when estimating the relative risk
    Sullivan, Thomas R.
    Lee, Katherine J.
    Ryan, Philip
    Salter, Amy B.
    [J]. BMC MEDICAL RESEARCH METHODOLOGY, 2017, 17
  • [5] BETA INSTABILITY WHEN INTEREST-RATE LEVELS CHANGE
    BILDERSEE, JS
    ROBERTS, GS
    [J]. JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS, 1981, 16 (03) : 375 - 380
  • [6] Multiple imputation when records used for imputation are not used or disseminated for analysis
    Reiter, Jerome P.
    [J]. BIOMETRIKA, 2008, 95 (04) : 933 - 946
  • [7] Multiple imputation in multivariate problems when the imputation and analysis models differ
    Schafer, JL
    [J]. STATISTICA NEERLANDICA, 2003, 57 (01) : 19 - 35
  • [8] A potential for bias when rounding in multiple imputation
    Horton, NJ
    Lipsitz, SR
    Parzen, M
    [J]. AMERICAN STATISTICIAN, 2003, 57 (04): : 229 - 232
  • [9] Bootstrap inference when using multiple imputation
    Schomaker, Michael
    Heumann, Hristian
    [J]. STATISTICS IN MEDICINE, 2018, 37 (14) : 2252 - 2266
  • [10] Should multiple imputation be stratified by exposure group when estimating causal effects via outcome regression?
    Zhang, Jiaxin
    Dashti, S. Ghazaleh
    Carlin, John B.
    Lee, Katherine J.
    Moreno-Betancur, Margarita
    [J]. INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 2021, 50 : 263 - 263
12345