Search Results - subject:"missing data"

Mapping risk factors of innovation activity enterprises

Golichenko, Oleg; Samovoleva, Svetlana - In: International Journal of Innovation and Regional Development 5 (2013) 2, pp. 149-164

The paper proposes a five-stage procedure to analyse risk factors of innovation activity. The system of innovation activity factors is determined at the first stage. The second stage identifies the factors that have a negative impact on innovation activity. At the third stage, the data of the...

Persistent link: https://www.econbiz.de/10010722738

A Bayesian model averaging approach to analyzing categorical data with nonignorable nonresponse

Janicki, Ryan; Malec, Donald - In: Computational Statistics & Data Analysis 57 (2013) 1, pp. 600-614

nonignorable models, and hence provides a better method for quantifying the additional uncertainty due to the missing data. …

Persistent link: https://www.econbiz.de/10010580852

Resistant estimators in Poisson and Gamma models with missing responses and an application to outlier detection

Bianco, Ana M.; Boente, Graciela; Rodrigues, Isabel M. - In: Journal of Multivariate Analysis 114 (2013) C, pp. 209-226

outlier detection rules. The focus of this paper is to define robust estimators for the regression parameter when missing data …

Persistent link: https://www.econbiz.de/10010594227

Illuminate the unknown: evaluation of imputation procedures based on the SAVE survey

Ziegelmeyer, Michael - In: AStA Advances in Statistical Analysis 97 (2013) 1, pp. 49-76

-Carlo simulation based on the observed data shows the superiority of the newly implemented smearing estimate to construct the missing … data structure. All waves are consistently imputed using the new method. Copyright Springer-Verlag 2013 …

Persistent link: https://www.econbiz.de/10010634369

Estimation of spatial panel data models with randomly missing data in the dependent variable

Wang, Wei; Lee, Lung-fei - In: Regional Science and Urban Economics 43 (2013) 3, pp. 521-538

We suggest and compare different methods for estimating spatial autoregressive panel models with randomly missing data …

Persistent link: https://www.econbiz.de/10010664711

Structurally missing data by OLS and Shapley Value regressions

Lipovetsky, Stan; Nowakowska, Ewa - In: International journal of operations and quantitative … 19 (2013) 3, pp. 169-178

Persistent link: https://www.econbiz.de/10010253596

Estimation of spatial panel data models with randomly missing data in the dependent variable

Wang, Wei; Lee, Lung-fei - In: Regional science & urban economics 43 (2013) 3, pp. 521-538

Persistent link: https://www.econbiz.de/10009746418

Model averaging with covariates that are missing completely at random

Zhang, Xinyu - In: Economics letters 121 (2013) 3, pp. 360-363

Persistent link: https://www.econbiz.de/10010391216

Sensitivity to missing data assumptions : theory and an evaluation of the US wage structure

Kline, Patrick; Santos, Andres - In: Quantitative economics : QE ; journal of the … 4 (2013) 2, pp. 231-267

Persistent link: https://www.econbiz.de/10010126200

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