摘要:

The literature on the analysis of incomplete data using models is reviewed in the context of nonresponse in sample surveys. The modeling approach provides a large body of methods for handling unit and item nonresponse, some of which cannot be derived from the randomization theory of inference for surveys. Key concepts from the literature on incomplete data, such as factorizations of the likelihood for special data patterns, the EM algorithm for general data patterns, and ignorability of the response mechanism, are discussed within the survey context. Model-based procedures are related to common methods for handling nonresponse in surveys, such as weighting or imputation of means within subclasses of the population.

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477792

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

摘要:

A method is developed for imputing missing values when the probability of response depends upon the variable being imputed. The missing data problem is viewed as one of parameter estimation in a regression model with stochastic censoring of the dependent variable. The prediction approach to imputation is used to solve this estimation problem. Wages and salaries are imputed to non-respondents in the Current Population Survey and the results are compared to the nonrespondents' IRS wage and salary data. The stochastic censoring approach gives improved results relative to a prediction approach that ignores the response mechanism.

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477793

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

摘要:

The robust regression method of Huber (1973) is used to fit a model to the cost of drilling for petroleum. Because the model includes a categorical variable (well type), a linear constraint is imposed on the parameter estimates Because the model was fit to the logarithm of cost and because it will be used to make repeated predictions of cost, an adjustment that approximately unbiases the predictions is imposed. The numerical values of the estimates are discussed, and a comparison is made with ordinary least squares.

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477794

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

摘要:

In many studies the values of one or more variables are missing for subsets of the original sample. This article focuses on the problem of obtaining maximum likelihood estimates (MLE) for the parameters of log-linear models under this type of incomplete data. The appropriate systems of equations are presented and the expectation-maximization (EM) algorithm (Dempster, Laird, and Rubin 1977) is suggested as one of the possible methods for solving them. The algorithm has certain advantages but other alternatives may be computationally more effective. Tests of fit for log-linear models in the presence of incomplete data are considered. The data from the Protective Services Project for Older Persons (Blenkner, Bloom, and Nielsen 1971; Blenkner, Bloom, and Weber 1974) are used to illustrate the procedures discussed in the article.

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477795

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

摘要:

Historical samples of military, naval, and merchant marine heights suffer from undercounts of short people, undercounts highly irregular compared to the truncated distributions for which standard methods are available. Our knowledge is too imprecise for parametric models of the undercount process but it suffices for intuitive description of the deviations from normality with which estimators should cope. Two new estimators are developed. The first adapts maximum likelihood for truncated normals to height histograms with gradual lower-tail shortfall. The second exploits bends in quantile-quantile plots. Standard error estimates based on Efron's bootstrap appear reliable. The estimators show average heights from British Royal Marine samples much shorter than their American opponents in the Revolutionary War and reveal a statistically significant increase by the 1820's in the British heights.

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477796

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477797

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477798

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477799

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477801

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor

ISSN:0162-1459    

DOI:10.1080/01621459.1982.10477802

出版商:Taylor & Francis Group    

年代:1982

数据来源: Taylor