Search | Korea Science

Kim, Ji-Hyun;Choi, Hye-Hyun
- Communications for Statistical Applications and Methods
- /
- v.9 no.3
- /
- pp.703-713
- /
- 2002
In longitudinal studies, outcomes are repeatedly measured over time for each subject. It is common to have missing values or dropouts for longitudinal data. In this study time trend in longitudinal data with dropouts is of concern. The confounding of time trend with dropout process is investigated through simulation studies. Some simulation results are reported for binary responses as well as continuous responses with patterns of dropouts varying. It has been found that time trend is not confounded with random dropout process for binary responses when it is estimated using GEE.
https://doi.org/10.5351/CKSS.2002.9.3.703 인용 PDF KSCI

Cho, Won-Seok;Kim, Heung-Gee;Kim, Yong-Gee
- Journal of the Korean Institute of Rural Architecture
- /
- v.9 no.1
- /
- pp.27-34
- /
- 2007
This study is to propose directions of waterfront planning about fishing village and harbor in East coast. Above all important waterfront-using in harbor, such as regional atmosphere and sea-scape are to investigate waterfront elements. For example, seaside park, harbor street mall, landmark, view point, promenade can be checked and design of waterfront may be possible to work out future harbor master plan. This study suggests that harbor of contemporary is to develop by regional waterfront characters. Accordingly, we analyze, it shows that the waterfront planning not only people of village but also visiting citizen is one of the important in developments about fishing village and harbor. As a results of this paper, we expect this research to be used as a valuable data in waterfront planning about fishing village and harbor.
PDF

Chixiang Chen;Biyi Shen;Ming Wang
- Communications for Statistical Applications and Methods
- /
- v.30 no.4
- /
- pp.355-368
- /
- 2023
This article introduces the R package ELCIC (https://cran.r-project.org/web/packages/ELCIC/index.html), which provides an empirical likelihood-based information criterion (ELCIC) for model selection that includes, but is not limited to, variable selection. The empirical likelihood is a semi-parametric approach to draw statistical inference that does not require distribution assumptions for data generation. Therefore, ELCIC is more robust and versatile in the context of model selection compared to the currently existing information criteria. This paper illustrates several applications of ELCIC, including its use in generalized linear models, generalized estimating equations (GEE) for longitudinal data, and weighted GEE (WGEE) for missing longitudinal data under the mechanisms of missing at random and dropout.
https://doi.org/10.29220/CSAM.2023.30.4.355 인용 PDF