Imputation Strategies for Incomplete Longitudinal Binary Data
碩士 === 淡江大學 === 統計學系碩士班 === 99 === It is very common for longitudinal studies to involve missing data. The imputation method is one of the effective procedures for handling with the problem of missing data. Based on the well-developed multiple imputation for normal responses and a random number gene...
Main Authors: | Tzu-Ying Li, 李紫熒 |
---|---|
Other Authors: | 陳怡如 |
Format: | Others |
Language: | en_US |
Published: |
2011
|
Online Access: | http://ndltd.ncl.edu.tw/handle/07067288866067263662 |
Similar Items
-
Longitudinal analysis of incomplete binary data /
by: Stern, Theresa Marie Papa
Published: (1997) -
Application of Multiple Imputation on the Statistical Analysis of Incomplete Data
by: Pi-Lin Liu, et al.
Published: (2010) -
Analysis of incomplete longitudinal binary responses with Bayesian method
by: Habibollah Esmaily, et al.
Published: (2015-10-01) -
Multiple imputation for analysis of incomplete data in distributed health data networks
by: Changgee Chang, et al.
Published: (2020-10-01) -
The impact of multiple imputation on incomplete rank data with missing covariates
by: LIU, TING-HSUAN, et al.
Published: (2014)