Accession Number : ADA114533

Title :   On Jointly Estimating Parameters and Missing Data by Maximizing the Complete-Data Likelihood.

Descriptive Note : Technical summary rept.,

Corporate Author : WISCONSIN UNIV-MADISON MATHEMATICS RESEARCH CENTER

Personal Author(s) : Little,Roderick J A ; Rubin,Donald B

PDF Url : ADA114533

Report Date : Feb 1982

Pagination or Media Count : 10

Abstract : One approach to handling incomplete data occasionally encountered in the literature is to treat the missing data as parameters and to maximize the complete data likelihood over missing data and parameters. This paper points out that although this approach can be useful in particular problems, it is not a generally reliable approach to the analysis of incomplete data. In particular, it does not share the optimal properties of maximum likelihood estimation, except under the trivial asymptotics in which the proportion of missing data goes to zero as the sample size increases. (Author)

Descriptors :   *Estimates, *Parameters, *Probability, *Mathematical analysis, Errors, Systems analysis, Reliability, Optimization, Asymptotic series, Data management, Plotting

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE