Results 171 to 180 of about 762,527 (191)
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Organizational Research Methods, 2007
Latent growth models implemented in multilevel models (MLM) or structural equation models (SEM) may be used to analyze longitudinal data with an emphasis on interindividual and intraindividual differences. The main objective of this study is to compare methods of handling missing time-invariant data under the assumption of missing completely at random.
M. Cheung
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Latent growth models implemented in multilevel models (MLM) or structural equation models (SEM) may be used to analyze longitudinal data with an emphasis on interindividual and intraindividual differences. The main objective of this study is to compare methods of handling missing time-invariant data under the assumption of missing completely at random.
M. Cheung
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Score test for missing at random or not under logistic missingness models
Biometrics, 2022Missing data are frequently encountered in various disciplines and can be divided into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR).
Hairu Wang, Zhiping Lu, Yukun Liu
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Indian Journal Of Agricultural Research, 2023
Background: The issue of missing data is prevalent in all type of research work, which can diminish statistical power and lead to inaccurate results if not managed correctly. Missing data cannot be ignored because every piece of data, no matter how small, affects the outcome significantly.
Sanju ., Vinay Kumar, Deepender .
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Background: The issue of missing data is prevalent in all type of research work, which can diminish statistical power and lead to inaccurate results if not managed correctly. Missing data cannot be ignored because every piece of data, no matter how small, affects the outcome significantly.
Sanju ., Vinay Kumar, Deepender .
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Behavior Genetics, 2008
In genetics study, the genotypes or phenotypes can be missing due to various reasons. In this paper, the impact of missing genotypes is investigated for high resolution combined linkage and association mapping of quantitative trait loci (QTL). We assume that the genotype data are missing completely at random (MCAR).
Ruzong, Fan +3 more
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In genetics study, the genotypes or phenotypes can be missing due to various reasons. In this paper, the impact of missing genotypes is investigated for high resolution combined linkage and association mapping of quantitative trait loci (QTL). We assume that the genotype data are missing completely at random (MCAR).
Ruzong, Fan +3 more
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Computational Statistics & Data Analysis, 2019
Two different methods for estimation, imputation and prediction for the functional linear model with scalar response when some of the responses are missing at random (MAR) are developed.
M. Febrero-Bande +2 more
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Two different methods for estimation, imputation and prediction for the functional linear model with scalar response when some of the responses are missing at random (MAR) are developed.
M. Febrero-Bande +2 more
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British Journal of Mathematical & Statistical Psychology, 2018
Moderation analysis is useful for addressing interesting research questions in social sciences and behavioural research. In practice, moderated multiple regression (MMR) models have been most widely used.
Qian Zhang, K. Yuan, Lijuan Wang
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Moderation analysis is useful for addressing interesting research questions in social sciences and behavioural research. In practice, moderated multiple regression (MMR) models have been most widely used.
Qian Zhang, K. Yuan, Lijuan Wang
semanticscholar +1 more source
STUDIES IN ENGINEERING AND EXACT SCIENCES
In this article, the authors investigate the properties of a local linear estimator for the expectile regression function in scenarios where the scalar response variable is missing at random, and the covariate is a functional variable. The study addresses the challenge of estimating the expectile regression function when the response variable is not ...
Zouaouia Boulenoir +3 more
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In this article, the authors investigate the properties of a local linear estimator for the expectile regression function in scenarios where the scalar response variable is missing at random, and the covariate is a functional variable. The study addresses the challenge of estimating the expectile regression function when the response variable is not ...
Zouaouia Boulenoir +3 more
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International Journal of Intelligent Engineering Informatics, 2023
P. Iris Punitha, J.G.R. Sathiaseelan
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P. Iris Punitha, J.G.R. Sathiaseelan
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International Journal of Intelligent Engineering Informatics, 2023
Iris Punitha P, J.G.R. Sathiaseelan
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Iris Punitha P, J.G.R. Sathiaseelan
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