Search Results - subject:"missing data mechanism"

On the regression method of estimation of population mean from incomplete survey data through imputation

Toutenburg, Helge - 2005

When some observations in the sample data are missing, the application of the regression method is considered for the estimation of population mean with and without the use of imputation. The performance properties of the estimators based on the methods of mean imputation, regression imputation...

Persistent link: https://www.econbiz.de/10010276841

Identifying missing data mechanisms in (2 x 2)-contingency tables

Nittner, Thomas; Toutenburg, Helge - 2004

Consider the sample of two binary variables X and Y with some missing structure within X or Y. The knowledge about the corresponding values of the observed covariate allows to play through all possible originally' complete data sets. After defining the notation, including some theoretical work,...

Persistent link: https://www.econbiz.de/10010276840

Data pruning in consumer choice models

Zanutto, Elaine; Bradlow, Eric - In: Quantitative Marketing and Economics 4 (2006) 3, pp. 267-287

from current academic Marketing literature) can lead to a nonignorable missing data mechanism. Secondly, we summarize an …

Persistent link: https://www.econbiz.de/10005701807

Missing data methods in official statistics in the United Kingdom: Some recent developments

Durrant, Gabriele - In: AStA Advances in Statistical Analysis 90 (2006) 4, pp. 577-593

Persistent link: https://www.econbiz.de/10005178809

Ergänzung fehlender Daten in Umfragen / Imputation of Missing Data in Surveys

Rässler, Susanne - In: Jahrbücher für Nationalökonomie und Statistik 220 (2000) 1, pp. 64-94

often seem to produce substantially biased estimates, when the missing-data mechanism is nonignorable. At least the …. Since these techniques rely at least implicitly on the assumption of the so-called ignorability of the missing-data … mechanism a simulation study is performed to investigate the power of several imputation techniques especially when the data are …

Persistent link: https://www.econbiz.de/10014608751

ML Estimation of Mean and Covariance Structures with Missing Data Using Complete Data Routines

Jamshidian, Mortaza; Bentler, Peter M. - In: Journal of Educational and Behavioral Statistics 24 (1999) 1, pp. 21-24

We consider maximum likelihood (ML) estimation of mean and covariance structure models when data are missing. Expectation maximization (EM), generalized expectation maximization (GEM), Fletcher-Powell, and Fisher-scoring algorithms are described for parameter estimation. It is shown how the...

Persistent link: https://www.econbiz.de/10010775986