A hybrid technique for the multiple imputation of survey data

Most of the background variables in MICS (Multiple Indicator Cluster Surveys) are categorical with many categories. Like many other survey data, the MICS 2014 women’s data suffers from a large number of missing values. Additionally, complex dependencies may be existent among a large number of categorical variables in such surveys. The most commonly used parametric multiple imputation (MI) approaches based on log linear models or chained Equations (MICE) become problematic in these situations and often the implemented algorithms fail. On the other hand, nonparametric MI techniques based on Bayesian latent class models worked very well if only categorical variables are considered. This article describes how chained equations MI for continuous variables can be made dependent on categorical variables which have been imputed beforehand by using latent class models. Root mean square errors (RMSEs) and coverage rates of 95% confidence intervals (CI) for generalized linear models (GLM’s) with binary response are estimated in a simulation study and a comparison is made among proposed and various existing MI methods. The proposed method outperforms the MICE algorithms in most of the cases with less computational time. The results obtained by the simulation study are supported by a real data example

PRINCIPAL COMPONENT ANALYSIS OF SOCIOECONOMIC FACTORS AND THEIR ASSOCIATION WITH LIFE EXPECTANCY AT BIRTH IN ASIA

ABSTRACT Life expectancy (LE) is considered as one of key health outcome and a major indicator of human development as well. Wide ranges of socioeconomic and demographic factors have major impact on life expectancy rate at birth in various countries. Association of several socioeconomic factors with life expectancy at birth and the influencing factors in forty countries of Asia has been explored in this paper. Less surprisingly the results and discussions obtained in this paper are in agreement with previous research. A close relationship between several socioeconomic variables and life expectancy at birth is found. Principal components analysis (PCA) and backward regression is performed on quantitative secondary data collected from various databases which shows that life expectancy at birth is statistically significant at 5% level of significance and have positive association with four factors extracted from PCA. Strong significant positive correlation is found between life expectancy at birth and health expenditures, gross national income, good governance and healthy life. However crude birth rate, crude death rate and infant mortality rate has negative relationship with life expectancy at birth which shows life expectancy at birth decreases as crude birth rate, crude death rate and infant mortality rate increases. The reference year for this study is 2012

Hybrid multiple imputation in a large scale complex survey

Large-scale complex surveys typically contain a large number of variables measured on an even larger number of respondents. Missing data is a common problem in such surveys. Since usually most of the variables in a survey are categorical, multiple imputation requires robust methods for modelling highdimensional categorical data distributions. This paper introduces the 3-stage Hybrid Multiple Imputation (HMI) approach, computationally efficient and easy to implement, to impute complex survey data sets that contain both continuous and categorical variables. The proposed HMI approach involves the application of sequential regression MI techniques to impute the continuous variables by using information from the categorical variables, already imputed by a non-parametric Bayesian MI approach. The proposed approach seems to be a good alternative to the existing approaches, frequently yielding lower root mean square errors, empirical standard errors and standard errors than the others. The HMI method has proven to be markedly superior to the existing MI methods in terms of computational efficiency. The authors illustrate repeated sampling properties of the hybrid approach using simulated data. The results are also illustrated by child data from the multiple indicator survey (MICS) in Punjab 2014

ARIA masterclass 2018: From guidelines to real-life implementation

Over the past 20 years, ARIA (Allergic Rhinitis and its Impact on Asthma) has developed various guidelines for the treatment of allergic rhinitis (AR) and asthma multimorbidity. Over time, the ARIA initiative has evolved to ensure the highest level of bestpractices adoption in real life settings. It has evolved towards Integrated Care Pathways (ICPs) using mobile technology, and has now entered a new phase in which change management is key to provide an active and healthy life to all AR patients. With that in mind, the first ARIA masterclass was held on 12th September 2018 in Brussels, Belgium. The masterclass aimed at informing clinicians about the principles of change management, providing unbiased education on diagnosis and treatments, sharing the most recent research data on AR and multimorbidities, and creating a snowball effect to increase the adoption of best practices around the globe. This report provides an overview of the ARIA masterclass concept, summarizes the key lectures and discussions, and gives an outline of the future key development.status: publishe

ARIA masterclass 2018 : from guidelines to real-life implementation

Over the past 20 years, ARIA (Allergic Rhinitis and its Impact on Asthma) has developed various guidelines for the treatment of allergic rhinitis (AR) and asthma multimorbidity. Over time, the ARIA initiative has evolved to ensure the highest level of best-practices adoption in real life settings. It has evolved towards Integrated Care Pathways (ICPs) using mobile technology, and has now entered a new phase in which change management is key to provide an active and healthy life to all AR patients. With that in mind, the first ARIA masterclass was held on 12th September 2018 in Brussels, Belgium. The masterclass aimed at informing clinicians about the principles of change management, providing unbiased education on diagnosis and treatments, sharing the most recent research data on AR and multimorbidities, and creating a snowball effect to increase the adoption of best practices around the globe. This report provides an overview of the ARIA masterclass concept, summarizes the key lectures and discussions, and gives an outline of the future key development