Search Results - subject:"missing data"

Fehlende Werte bei korrelierten Beobachtungen

Kastner, Christian - 2001

Persistent link: https://www.econbiz.de/10001530431

Fehlende Kovariablenwerte bei linearen Regressionsmodellen

Fieger, Andreas - 2001

Persistent link: https://www.econbiz.de/10001526685

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

inference is intended to the population of all cases rather than the population of cases with no missing data. Therefore a … variety of techniques to fill in missing data with plausible values have been developed and are offered to a broad audience in …. Since these techniques rely at least implicitly on the assumption of the so-called ignorability of the missing-data …

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

Imputation Methods for Incomplete Dependent Variables in Finance

Kofman, Paul; Sharpe, Ian - Finance Discipline Group, Business School - 2000

independent variables are completely observed. These methods are compared by simulation to commonly applied alternative missing … data methodologies in the finance literature. The methods are then applied to a system of simultaneous equations modelling …

Persistent link: https://www.econbiz.de/10005102341

An estimate of the covariance between variables which are not jointly observed

Cudeck, Robert - In: Psychometrika 65 (2000) 4, pp. 539-546

Persistent link: https://www.econbiz.de/10005603388

An iterative estimating procedure for probit-type nonresponse models in surveys with call backs

Anido, Carmen; Valdés, Teófilo - In: TEST: An Official Journal of the Spanish Society of … 9 (2000) 1, pp. 233-253

Persistent link: https://www.econbiz.de/10005166813

Imputation of Missing Item Responses: Some Simple Techniques

Huisman, Mark - In: Quality & Quantity: International Journal of Methodology 34 (2000) 4, pp. 331-351

Persistent link: https://www.econbiz.de/10009396272

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

well as the mean imputed and listwise deletion estimates to missing data mechanisms is investigated using three artificial …

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

Applications and Extensions of MCMC in IRT: Multiple Item Types, Missing Data, and Rated Responses

Patz, Richard J.; Junker, Brian W. - In: Journal of Educational and Behavioral Statistics 24 (1999) 4, pp. 342-366

Patz and Junker (1999) describe a general Markov chain Monte Carlo (MCMC) strategy, based on Metropolis-Hastings sampling, for Bayesian inference in complex item response theory (IRT) settings. They demonstrate the basic methodology using the two-parameter logistic (2PL) model. In this paper we...

Persistent link: https://www.econbiz.de/10010775999

Sample Size Estimation for Longitudinal Designs with Attrition: Comparing Time-Related Contrasts Between Two Groups

Hedeker, Donald; Gibbons, Robert D.; Waternaux, Christine - In: Journal of Educational and Behavioral Statistics 24 (1999) 1, pp. 70-93

Formulas for estimating sample sizes are presented to provide specified levels of power for tests of significance from a longitudinal design allowing for subject attrition. These formulas are derived for a comparison of two groups in terms of single degree-of-freedom contrasts of population...

Persistent link: https://www.econbiz.de/10010776007