【摘 要】
：
It is very common that a set of quantitative data is incomplete, especially in lougitudinal studies.For example, subjects may drop out before the study term
【机 构】
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School of Mathematics, The University of Manchester Oxford Road, Manchester M13 9PL, U.K.
【出 处】
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The Third IMS-China International Conference on Statistics a
论文部分内容阅读
It is very common that a set of quantitative data is incomplete, especially in lougitudinal studies.For example, subjects may drop out before the study terminates,which leads to the unavailability of the information after the time of dropout.It is very well known that missing data can cause serious bias and lead to ineffcient estimation for the mean parameters if the missing mechanism is not taken into account (Afifi Elashoff, 1966; Rubin, 1976).
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