Search Results - subject:"missing data"

DATA ENVELOPMENT ANALYSIS WITH MISSING DATA: A MULTIPLE LINEAR REGRESSION ANALYSIS APPROACH

CHEN, YA; LI, YONGJUN; WU, HUAQING; LIANG, LIANG - In: International Journal of Information Technology & … 13 (2014) 01, pp. 137-153

Data envelopment analysis (DEA) assumes that the data set is precise when performing efficiency evaluation of peer decision making units (DMUs). The current paper proposes a multiple linear regression analysis (MLRA) approach to estimate missing values if some of the entries in the data set are...

Persistent link: https://www.econbiz.de/10010748344

Multiple Imputation: an attempt to retell the evolutionary process

Meinfelder, Florian - In: AStA Wirtschafts- und Sozialstatistisches Archiv 8 (2014) 4, pp. 249-267

to give a rough overview of the shortcomings of methods for handling missing data prior to Rubin’s work in the late 1970s …Multiple Imputation describes a strategy for analyzing incomplete data that accounts for uncertainty in the missing … data by replacing (imputing) each missing value by several ‘candidates’. The actual implementation of any Multiple …

Persistent link: https://www.econbiz.de/10011151282

A Class of Distribution-Free Models for Longitudinal Mediation Analysis

Gunzler, D.; Tang, W.; Lu, N.; Wu, P.; Tu, X. - In: Psychometrika 79 (2014) 4, pp. 543-568

information they provide in real study applications. In particular, in longitudinal studies missing data is commonly addressed … under the assumption of missing at random (MAR), where current methods are unable to handle such missing data if parametric … longitudinal mediation analysis under the two most popular missing data mechanisms; missing completely at random (MCAR) and missing …

Persistent link: https://www.econbiz.de/10011151907

Comments on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates

Visser, Ingmar; Speekenbrink, Maarten - In: TEST: An Official Journal of the Spanish Society of … 23 (2014) 3, pp. 478-483

Bartolucci et al. (Test, <CitationRef CitationID="CR1">2014</CitationRef>) provide a nice showcase of the flexibility of latent Markov models for longitudinal data. Indeed, their list of applications is impressive and includes a wide variety of models, with covariates to model transitions between latent states and direct effects on the...</citationref>

Persistent link: https://www.econbiz.de/10010994306

Global environmental emissions estimate: application of multiple imputation

Miyama, Eriko; Managi, Shunsuke - In: Environmental Economics and Policy Studies 16 (2014) 2, pp. 115-135

A new database called the World Resource Table is constructed in this study. Missing values are known to produce complications when constructing global databases. This study provides a solution for applying multiple imputation techniques and estimates the global environmental Kuznets curve (EKC)...

Persistent link: https://www.econbiz.de/10010994481

Focused vector information criterion model selection and model averaging regression with missing response

Sun, Zhimeng; Su, Zhi; Ma, Jingyi - In: Metrika 77 (2014) 3, pp. 415-432

In this paper, a focused vector information criterion for model selection and model averaging is considered for the linear model with missing response. Based on the focused information criterion of Hjort and Claeskens (J Am Stat Assoc 98:879–945, <CitationRef CitationID="CR12">2003</CitationRef>) and imputation idea, a frequentist model...</citationref>

Persistent link: https://www.econbiz.de/10010995127

Comparison of Two Different Adaptive Neuro-Fuzzy Inference Systems in Modelling Daily Reference Evapotranspiration

Kisi, Ozgur; Zounemat-Kermani, Mohammad - In: Water Resources Management 28 (2014) 9, pp. 2655-2675

effective variable in modeling ET <Subscript> 0 </Subscript>. In the second part of the study, the effect of missing data on … affected by missing data while the test accuracy of the ANFIS-SC model slightly decreases by increasing missing data’s percent …

Persistent link: https://www.econbiz.de/10010997806

Statistical study of asymmetry in cell lineage data

de Saporta, Benoîte; Gégout-Petit, Anne; Marsalle, … - In: Computational Statistics & Data Analysis 69 (2014) C, pp. 15-39

A rigorous methodology is proposed to study cell division data consisting in several observed genealogical trees of possibly different shapes. The procedure takes into account missing observations, data from different trees, as well as the dependence structure within genealogical trees. Its main...

Persistent link: https://www.econbiz.de/10010709955

Robust growth mixture models with non-ignorable missingness: Models, estimation, selection, and application

Lu, Zhenqiu; Zhang, Zhiyong - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 220-240

Challenges in the analyses of growth mixture models include missing data, outliers, estimation, and model selection …. Four non-ignorable missingness models to recover the information due to missing data, and three robust models to reduce the …

Persistent link: https://www.econbiz.de/10010719680

Global environmental emissions estimate : application of multiple imputation

Miyama, Eriko; Managi, Shunsuke - In: Environmental economics and policy studies 16 (2014) 2, pp. 115-135

Persistent link: https://www.econbiz.de/10010351424