Results 1 to 10 of about 1,064,736 (168)
International Journal of Population Data Science, 2022 To create a dataset which describes the care experience of children in Scotland data. To share with analysts in a safe setting to allow linkage, and provide information on the strengths and weaknesses.
Cecilia Macintyre, Gillian Raab
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Scientific Reports, 2022 Little is known about the within-person variability of different frailty instruments, their agreement over time, and whether use of repeat assessments could improve the strength of associations with adverse health outcomes.
Dani J. Kim +6 more
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International Journal of Population Data Science, 2023 Introduction Trusted Research Environments (TREs) are secure computing environments that provide access to data for approved researchers to use in studies that can save and improve lives.
Rachel Brophy +12 more
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Frontiers in Psychology, 2023 PurposePhysical fitness and fundamental motor skills are two important aspects for the healthy development of preschoolers. Despite the growing interest in clarifying their relationship, the scarcity of longitudinal studies prevents us from understanding
Jiebo Chen +5 more
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Ignorability for general longitudinal data [PDF]
Biometrika, 2017 Likelihood factors that can be disregarded for inference are termed ignorable. We demonstrate that close ties exist between ignorability and identification of causal effects by covariate adjustment. A graphical condition, stability, plays a role analogous to that of missingness at random, but is applicable to general longitudinal data.
Farewell, D. M., Huang, C., Didelez, V.
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Learning loss and learning inequality during the Covid-19 pandemic
Ensaio, 2023 This paper evaluates the effects of school closure during the Covid-19 pandemic on learning loss and learning inequalities in Rio de Janeiro. It presents longitudinal data for 671 children (5/6 years old) enrolled in the second year of preschool ...
Tiago Lisboa Bartholo +2 more
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Longitudinal functional data analysis [PDF]
Stat, 2015 We consider dependent functional data that are correlated because of a longitudinal‐based design: each subject is observed at repeated times and at each time, a functional observation (curve) is recorded. We propose a novel parsimonious modelling framework for repeatedly observed functional observations that allows to extract low‐dimensional features ...
So Young Park, Ana-Maria Staicu
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Measurement in Intensive Longitudinal Data
Structural Equation Modeling: A Multidisciplinary Journal, 2021 Technological advances have increased the prevalence of intensive longitudinal data as well as statistical techniques appropriate for these data, such as dynamic structural equation modeling (DSEM). Intensive longitudinal designs often investigate constructs related to affect or mood and do so with multiple item scales.
Daniel McNeish +3 more
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Survey Research Methods, 2022 We explore the pattern, potential drivers, and implications of item non-response on survey questions about domestic abuse. We draw on a longitudinal representative prospective survey on children and their families in Scotland (N:3646) and use ...
Valeria Skafida +2 more
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Analysis of longitudinal metabolomics data [PDF]
Bioinformatics, 2004 Abstract Motivation: Metabolomics datasets are generally large and complex. Using principal component analysis (PCA), a simplified view of the variation in the data is obtained. The PCA model can be interpreted and the processes underlying the variation in the data can be analysed.
Jansen, J.J. +4 more
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