Search results for " Imputation"
showing 10 items of 23 documents
Edge-Based Missing Data Imputation in Large-Scale Environments
2021
Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis
Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error
2018
Skin affections after sulfur mustard (SM) exposure include erythema, blister formation and severe inflammation. An antidote or specific therapy does not exist. Anti-inflammatory compounds as well as substances counteracting SM-induced cell death are under investigation. In this study, we investigated the benzylisoquinoline alkaloide berberine (BER), a metabolite in plants like berberis vulgaris, which is used as herbal pharmaceutical in Asian countries, against SM toxicity using a well-established in vitro approach. Keratinocyte (HaCaT) mono-cultures (MoC) or HaCaT/THP-1 co-cultures (CoC) were challenged with 100, 200 or 300 mM SM for 1 h. Post-exposure, both MoC and CoC were treated with 1…
Haplotype reference consortium panel: Practical implications of imputations with large reference panels.
2017
Contains fulltext : 177754.pdf (Publisher’s version ) (Open Access) Recently, the Haplotype Reference Consortium (HRC) released a large imputation panel that allows more accurate imputation of genetic variants. In this study, we compared a set of directly assayed common and rare variants from an exome array to imputed genotypes, that is, 1000 genomes project (1000GP) and HRC. We showed that imputation using the HRC panel improved the concordance between assayed and imputed genotypes at common, and especially, low-frequency variants. Furthermore, we performed a genome-wide association meta-analysis of vertical cup-disc ratio, a highly heritable endophenotype of glaucoma, in four cohorts usin…
Construction of quality of life change patterns: example in oncology in a phase III therapeutic trial (FFCD 0307)
2015
Objective Quality of life data in cancerology are often difficult to summarize due to missing data and difficulty to analyze the pattern of evolution in different groups of patients. The aim of this work was to apply a new methodology to construct Quality of Life (QoL) change patterns within patients included in a clinical trial comparing to regimen of treatment in locally advanced eosogastric cancer. Materials and methods In this trial, QoL was assessed every 2 months by self-reported EORTC QLQ-C30 questionnaire. Physical dimension scores were analyzed. After multiple imputation of missing data, 27 statistical measures aiming to describe the variation of QoL measures among follow-up were c…
Cost-description and multiple imputation of missing values: theSATisfaction and adherence to COPD treatment(SAT) study
2018
Aim:This article reports on a retrospective quarterly cost description (CD) performed on 401 patients with stable chronic obstructive pulmonary disease (COPD) at enrolment in the national, multicen...
Regression imputation for Space-Time datasets with missing values
2009
Data consisting in repeated observations on a series of fixed units are very common in different context like biological, environmental and social sciences, and different terminology is often used to indicate this kind of data: panel data, longitudinal data, time series-cross section data (TSCS), spatio-temporal data. Missing information are inevitable in longitudinal studies, and can produce biased estimates and loss of powers. The aim of this paper is to propose a new regression (single) imputation method that, considering the particular structure and characteristics of the data set, creates a “complete” data set that can be analyzed by any researcher on different occasions and using diff…
Regression with imputed covariates: A generalized missing-indicator approach
2011
A common problem in applied regression analysis is that covariate values may be missing for some observations but imputed values may be available. This situation generates a trade-off between bias and precision: the complete cases are often disarmingly few, but replacing the missing observations with the imputed values to gain precision may lead to bias. In this paper, we formalize this trade-off by showing that one can augment the regression model with a set of auxiliary variables so as to obtain, under weak assumptions about the imputations, the same unbiased estimator of the parameters of interest as complete-case analysis. Given this augmented model, the bias-precision trade-off may the…
Genome-wide Analyses Identify KIF5A as a Novel ALS Gene
2018
© 2018 Elsevier Inc.
Polygenic Risk Scores and Physical Activity
2020
Supplemental digital content is available in the text.
L'imputazione dei dati mancanti: l'effetto sui parametri di un Extended Logistic Rasch Model
2008
Il problema dei dati mancanti è abbastanza comune nella ricerca empirica, specialmente nelle scienze sociali in cui il tentativo di misurazione di quantità non direttamente osservabili (variabili latenti)avviene attraverso la somministrazione di test o questionari costituiti da più item. I modelli statistici finalizzati alla soluzione di tale problema richiedono, in genere, un elevato numero di osservazioni per ogni unità coinvolta nell’analisi. In un contesto multivariato il problema si amplifica, poiché nel modello sono considerati più item per ciascuna osservazione: la probabilità, quindi, di avere almeno un dato mancante non è irrilevante ed è, inoltre, crescente al crescere del numero …