ANOVA FOR LONGITUDINAL DATA WITH MISSING VALUES

被引：9

作者：

Chen, Song Xi ^{[1
,2
]}

Zhong, Ping-Shou ^{[1
]}

机构：

[1] Iowa State Univ, Dept Stat, Ames, IA 50011 USA

[2] Peking Univ, Ctr Stat Sci, Guanghua Sch Management, Beijing 100871, Peoples R China

来源：

ANNALS OF STATISTICS | 2010年 / 38卷 / 06期

关键词：

Analysis of variance; empirical likelihood; kernel smoothing; missing at random; semiparametric model; treatment effects; SEMIPARAMETRIC REGRESSION-ANALYSIS; VARYING-COEFFICIENT MODEL; EMPIRICAL LIKELIHOOD; BOOTSTRAP; TESTS;

D O I：

10.1214/10-AOS824

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：

We carry out ANOVA comparisons of multiple treatments for longitudinal studies with missing values. The treatment effects are modeled semiparametrically via a partially linear regression which is flexible in quantifying the time effects of treatments. The empirical likelihood is employed to formulate model-robust nonparametric ANOVA tests for treatment effects with respect to covariates, the nonparametric time-effect functions and interactions between covariates and time. The proposed tests can be readily modified for a variety of data and model combinations, that encompasses parametric, semiparametric and nonparametric regression models; cross-sectional and longitudinal data, and with or without missing values.

引用

页码：3630 / 3659

页数：30

共 50 条

[21] Bayesian Test of Homogeneity in Transition Model for Longitudinal Ordinal Response Data with Missing Values
S. Noorian
M. Ganjali
[J]. Journal of Statistical Theory and Applications, 2013, 12 (2): : 191 - 199
[22] Analysis of longitudinal data with non-ignorable non-monotone missing values
Troxel, AB
Harrington, DP
Lipsitz, SR
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 1998, 47 : 425 - 438
[23] EMPIRICAL LIKELIHOOD APPROACH FOR LONGITUDINAL DATA WITH MISSING VALUES AND TIME-DEPENDENT COVARIATES
Yan Zhang
Weiping Zhang
Xiao Guo
[J]. Annals of Applied Mathematics, 2016, 32 (02) : 200 - 220
[24] Imputation-based strategies for clinical trial longitudinal data with nonignorable missing values
Yang, Xiaowei
Li, Jinhui
Shoptaw, Steven
[J]. STATISTICS IN MEDICINE, 2008, 27 (15) : 2826 - 2849
[25] ANALYSIS OF DATA WITH MISSING VALUES - COMMENTARY
LITTLE, RJA
[J]. STATISTICS IN MEDICINE, 1988, 7 (1-2) : 347 - 355
[26] Handling missing values in trait data
Johnson, Thomas F.
Isaac, Nick J. B.
Paviolo, Agustin
Gonzalez-Suarez, Manuela
[J]. GLOBAL ECOLOGY AND BIOGEOGRAPHY, 2021, 30 (01): : 51 - 62
[27] ANALYSIS OF DATA WITH MISSING VALUES - DISCUSSION
HELMS, RW
LAIRD, NM
LEBOWITZ, MD
MANTEL, N
LOUIS, TA
WU, M
[J]. STATISTICS IN MEDICINE, 1988, 7 (1-2) : 357 - 360
[28] Missing values in monotone data sets
Popova, Viara
[J]. ISDA 2006: Sixth International Conference on Intelligent Systems Design and Applications, Vol 1, 2006, : 627 - 632
[29] SPECTRA FROM DATA WITH MISSING VALUES
HARRIS, RW
[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1987, 1 (01) : 97 - 104
[30] Analysing censored longitudinal data with non-ignorable missing values: depression in older age
Falcaro, Milena
Pendleton, Neil
Pickles, Andrew
[J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, 2013, 176 (02) : 415 - 430

← 1 2 3 4 5 →