Search Results - subject:"missing data"

Estimating discrete Markov models from various incomplete data schemes

Pasanisi, Alberto; Fu, Shuai; Bousquet, Nicolas - In: Computational Statistics & Data Analysis 56 (2012) 9, pp. 2609-2625

distributions of the transition probabilities in this missing-data framework. Leaning on the dependence between the rows of the …

Persistent link: https://www.econbiz.de/10010577740

Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation

Corsi, Fulvio; Peluso, Stefano; Audrino, Francesco - School of Economics and Political Science, Universität … - 2012

, we model noisy and asynchronous ultra-high-frequency asset prices in a state-space framework with missing data. We then … the expectation step, by means of the Kalman filter with missing data, we reconstruct the smoothed and synchronized series …

Persistent link: https://www.econbiz.de/10009653426

Class Attendance and Students’ Evaluations of Teaching

Wolbring, Tobias - In: Evaluation Review 36 (2012) 1, pp. 72-96

adjust for absenteeism, change course rankings? Research Design: The author discusses the problem from a missing data …

Persistent link: https://www.econbiz.de/10010553091

The Effects of Auxiliary Variables on Coefficient Bias and Efficiency in Multiple Imputation

Mustillo, Sarah - In: Sociological Methods & Research 41 (2012) 2, pp. 335-361

to the variable/varaibles being imputed, and extraneous variables); (b) three levels of missing data (10 percent, 20 … efficiency in this simulation, regardless of the amount of missing data or the assumption of missing. Hence, the inclusion of …

Persistent link: https://www.econbiz.de/10010614756

Root-n estimability of some missing data models

Yuan, Ao; Xu, Jinfeng; Zheng, Gang - In: Journal of Multivariate Analysis 106 (2012) C, pp. 147-166

It is known that in many missing data models, for example, survival data models, some parameters are root-n estimable … preliminary assessments of the root-n estimability in these models. In this article, we study this problem for four missing data …

Persistent link: https://www.econbiz.de/10010572283

Diagnostics for multiple imputation in Stata

Eddings, Wesley; Marchenko, Yulia - In: Stata Journal 12 (2012) 3, pp. 353-367

Our new command midiagplots makes diagnostic plots for multiple imputations created by mi impute. The plots compare the distribution of the imputed values with that of the observed values so that problems with the imputation model can be corrected before the imputed data are analyzed. We include...

Persistent link: https://www.econbiz.de/10010631452

Fehlende Werte in den Sozialwissenschaften : Analyse und Korrektur mit Beispielen aus dem ALLBUS

Messingschlager, Martin - 2012

Persistent link: https://www.econbiz.de/10009759550

Nonparametric inference for unbalanced time series data

Linton, Oliver Bruce - 2004

problem of missing data. We also discuss effciency and power. Unbalanced data of the type we consider are quite common in …

Persistent link: https://www.econbiz.de/10010318468

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

Multiple imputation for unit-nonresponse versus weighting including a comparison with a nonresponse follow-up study

Rässler, Susanne; Schnell, Rainer - 2004

The results of a national fear of crime survey are compared with results following the use of different nonresponse correction procedures. We compared naive estimates, weighted estimates, estimates after a thorough nonresponse follow-up and estimates after multiple imputation. A strong...

Persistent link: https://www.econbiz.de/10010299820