Australia’s statistics are of a high quality. Based on the review of its statistical practices, a set of recommendations is presented designed to increase its adherence to internationally accepted statistical practices. The aim of the review is to enhance the usefulness of...

This report on the Observance of Standards and Codes on Data Module for Indonesia highlights that the Indonesian statistical system is undergoing fundamental transition. The statistical agencies are dealing with important challenges. They are at various stages of adopting and implementing...

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...

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested...

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested...

This paper introduces two new commands, smpred and smmatch, that implement the statistical matching procedure proposed by Rubin (1986). The purpose of statistical matching in Rubin's procedure is to generate a single dataset from various datasets, where each dataset contains a specific variable...

A new database called the World Resource Table (WRT) 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...

Missing data is a very frequent obstacle in many social science studies. The absence of values on one or more variables can signi?cantly affect statistical analyses by reducing their precision and by introducing selection biases. Being unable to account for these aspects may result in severe...

Previous studies that analyzed multiple imputation using survey data did not take into account the survey sampling design. The objective of the current study is to analyze the impact of survey sampling design missing data imputation, using multivariate multiple imputation method. The results of...