Buscar
Mostrando ítems 11-20 de 606
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 ...
Imputation of Rainfall Data Using the Sine Cosine Function Fitting Neural Network
Missing rainfall data have reduced the quality of hydrological data analysis because they are the essential input for hydrological modeling. Much research has focused on rainfall data imputation. However, the compatibility ...
Estimation of Spatial Lag Model Under Random Missing Data in the Dependent Variable. Two Stage Estimator with Imputation
(Pontificia Universidad Católica del PerúPE, 2022)
Estimation of Spatial Lag Model Under Random Missing Data in the Dependent Variable. Two Stage Estimator with Imputation
(Pontificia Universidad Católica del Perú. Fondo EditorialPE, 2021)
Handling missing values in trait data
(Wiley Blackwell Publishing, Inc, 2021-01)
Aim: Trait data are widely used in ecological and evolutionary phylogenetic comparative studies, but often values are not available for all species of interest. Traditionally, researchers have excluded species without data ...