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Use of data imputation tools to reconstruct incomplete air quality datasets: A case-study in Temuco, Chile
(Elsevier Ltd, 2019)
© 2018 Elsevier LtdMissing data from air quality datasets is a common problem, but is much more severe in small cities or localities. This poses a great challenge for environmental epidemiology as high exposures to pollutants ...
Multiple imputation using chained equations for missing data in TIMSS: a case study
(Springer, 2013)
In this paper, we document a study that involved applying a multiple imputation technique with chained equations to data drawn from the 2007 iteration of the TIMSS database. More precisely, we imputed missing variables ...
Multiple imputation using chained equations for missing data in TIMSS: a case study
(Springer, 2013)
In this paper, we document a study that involved applying a multiple imputation technique with chained equations to data drawn from the 2007 iteration of the TIMSS database. More precisely, we imputed missing variables ...
A strategy to impute age at onset of a particular condition from external sources
(SAGE Publications Ltd, 2021)
© The Author(s) 2021.A key hypothesis in epidemiological studies is that time to disease exposure provides relevant information to be considered in statistical models. However, the initiation time of a particular condition ...
Computational aspects of nonparametric Bayesian analysis with applications to the modeling of multiple binary sequences
(AMER STATISTICAL ASSOC, 2000)
We consider Markov mixture models for multiple longitudinal binary sequences. Prior uncertainty in the mixing distribution is characterized by a Dirichlet process centered on a matrix beta measure. We use this setting to ...
Multiple imputation procedures allow the rescue of missing data: An application to determine serum tumor necrosis factor (TNF) concentration values during the treatment of rheumatoid arthritis patients with anti-TNF therapy
(Sociedad de Biología de Chile, 2005)
Longitudinal studies aimed at evaluating patients clinical response to specific therapeutic treatments are frequently summarized in incomplete datasets due to missing data. Multivariate statistical procedures use only ...
Breast cancer and modifiable lifestyle factors in argentinean women: Addressing missing data in a case-control study
(Asian Pacific Organization Cancer Prevention, 2016-10)
A number of studies have evidenced the effect of modifiable lifestyle factors such as diet, breastfeeding and nutritional status on breast cancer risk. However, none have addressed the missing data problem in nutritional ...