South African household surveys typically contain coarsened earnings data, which consist of a mixture of missing earnings values, point responses and interval-censored responses. This paper uses sequential regression multivariate imputation to impute missing and interval-censored values in the...

The predictive likelihood is of particular relevance in a Bayesian setting when the purpose is to rank models in a forecast comparison exercise. This paper discusses how the predictive likelihood can be estimated for any subset of the observable variables in linear Gaussian state-space models...

This paper considers three ratio estimators of the population mean using known correlation coefficient between the study and auxiliary variables in simple random sample when some sample observations are missing. The suggested estimators are compared with the estimators of Singh and Horn (Metrika...

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>

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)...

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>

This study compares two different adaptive neuro-fuzzy inference systems, adaptive neuro-fuzzy inference system (ANFIS) with grid partition (GP) method and ANFIS with subtractive clustering (SC) method, in modeling daily reference evapotranspiration (ET <Subscript> 0 </Subscript>). Daily climatic data including air...</subscript>

Despite wide applications of both mediation models and missing data techniques, formal discussion of mediation analysis with missing data is still rare. We introduce and compare four approaches to dealing with missing data in mediation analysis including listwise deletion, pairwise deletion,...

Patient-reported outcome measures (PROMs) are now routinely collected in the English National Health Service (NHS) and used to compare and reward hospital performance within a high-powered pay-for-performance scheme. However, PROMs are prone to missing data. For example, hospitals often fail to...