南方科技大学知识苑(SUSTech KC): Valid statistical inference methods for incomplete contingency table with three-category missing data

题名	Valid statistical inference methods for incomplete contingency table with three-category missing data
作者	Huang，Xifen 1; Liang，Jiajuan 2; Tian，Guo Liang3
通讯作者	Huang，Xifen
发表日期	2021
DOI	10.1080/03610918.2021.1977953
发表期刊	COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 影响因子和分区
ISSN	0361-0918
EISSN	1532-4141
卷号	52 期号:11
摘要	Missing observations in r × c contingency tables often occur in medical, bio-pharmaceutical and epidemiological researches. The most common method to analyze incomplete contingency tables simply removes the non-response counts from both variables or depends on an independence assumption, which may be improper and could result in unreliable conclusions because of the under-estimation of the uncertainty. In this article, we first derive the valid sampling distribution of the observed counts by taking three categories missing data into consideration under the assumption of missing at random and the assumption of the total number of observations being fixed. Next, based on the new sampling distribution, the Fisher scoring algorithm for calculating the maximum likelihood estimates of parameters is developed, and the small-sample bootstrap confidence interval method is also provided. In addition, we theoretically compare the proposed sampling distribution with two existing sampling distributions, and conduct some simulations to investigate the performance of the three different sampling distributions in statistical inferences. Finally, two real data sets are analyzed to illustrate the newly proposed sampling distribution and corresponding statistical methods.
关键词	Bootstrap methods Categorical random variable Incomplete contingency tables Missing at random Valid sampling distribution
相关链接	[Scopus记录]
收录类别	SCI ; EI
语种	英语
学校署名	其他
资助项目	National Natural Science Foundation of China["11901515","11771199"] ; United International College (UIC) Start-up Research Fund[R72021106]
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000697401500001
出版者	TAYLOR & FRANCIS INC
EI入藏号	20213810925927
EI主题词	Maximum likelihood estimation ; Uncertainty analysis
EI分类号	Statistical Methods:922 ; Probability Theory:922.1
ESI学科分类	MATHEMATICS
Scopus记录号	2-s2.0-85115223083
来源库	Scopus
引用统计	被引频次[WOS]：0
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/253620
专题	理学院_统计与数据科学系
作者单位	1.School of Mathematics,Yunnan Normal University,Kunming,China 2.Division of Science and Technology,BNU–HKBU United International College,Zhuhai,China 3.Department of Statistics and Data Science,Southern University of Science and Technology,Shenzhen,China
推荐引用方式 GB/T 7714	Huang，Xifen,Liang，Jiajuan,Tian，Guo Liang. Valid statistical inference methods for incomplete contingency table with three-category missing data[J]. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION,2021,52(11).
APA	Huang，Xifen,Liang，Jiajuan,&Tian，Guo Liang.(2021).Valid statistical inference methods for incomplete contingency table with three-category missing data.COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION,52(11).
MLA	Huang，Xifen,et al."Valid statistical inference methods for incomplete contingency table with three-category missing data".COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 52.11(2021).