Search results for "multiple imputation"
showing 8 items of 8 documents
Factors Influencing Teachers’ Use of ICT in Class: Evidence from a Multilevel Logistic Model
2022
Information and Communication Technologies (ICTs) have become a key factor in the educational context, especially in the aftermath of the COVID-19 pandemic, and, correctly implemented, can help to improve academic performance. The aim of this research was to analyse the factors that influence teachers’ decisions to use ICT more- or less frequently to carry out tasks and exercises in their classes. To this end, we estimated a multilevel logistic model with census data from the individualized evaluation of students of the Community of Madrid (Spain) carried out at the end of the 2018–2019 academic year in primary and secondary education. Additionally, we applied multiple imputation techniques…
Bayesian models for data missing not at random in health examination surveys
2018
In epidemiological surveys, data missing not at random (MNAR) due to survey nonresponse may potentially lead to a bias in the risk factor estimates. We propose an approach based on Bayesian data augmentation and survival modelling to reduce the nonresponse bias. The approach requires additional information based on follow-up data. We present a case study of smoking prevalence using FINRISK data collected between 1972 and 2007 with a follow-up to the end of 2012 and compare it to other commonly applied missing at random (MAR) imputation approaches. A simulation experiment is carried out to study the validity of the approaches. Our approach appears to reduce the nonresponse bias substantially…
Identification of patterns og change on mongitudinal data, illustrated by two exemples : study of hospital pathways in the management of cancer. Cons…
2014
Context In healthcare domain, data mining for knowledge discovery represent a growing issue. Questions about the organisation of healthcare system and the study of the relation between treatment and quality of life (QoL) perceived could be addressed that way. The evolution of technologies provides us with efficient data mining tools and statistical packages containing advanced methods available for non-experts. We illustrate this approach through two issues: 1 / What organisation of healthcare system for cancer diseases management? 2 / Exploring in patients suffering from metastatic cancer, the relationship between health-related QoL perceived and treatment received as part of a clinical tr…
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...
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…
Selection bias was reduced by recontacting nonparticipants
2016
Objective One of the main goals of health examination surveys is to provide unbiased estimates of health indicators at the population level. We demonstrate how multiple imputation methods may help to reduce the selection bias if partial data on some nonparticipants are collected. Study Design and Setting In the FINRISK 2007 study, a population-based health study conducted in Finland, a random sample of 10,000 men and women aged 25–74 years were invited to participate. The study included a questionnaire data collection and a health examination. A total of 6,255 individuals participated in the study. Out of 3,745 nonparticipants, 473 returned a simplified questionnaire after a recontact. Both…
Systematic handling of missing data in complex study designs : experiences from the Health 2000 and 2011 Surveys
2016
We present a systematic approach to the practical and comprehensive handling of missing data motivated by our experiences of analyzing longitudinal survey data. We consider the Health 2000 and 2011 Surveys (BRIF8901) where increased non-response and non-participation from 2000 to 2011 was a major issue. The model assumptions involved in the complex sampling design, repeated measurements design, non-participation mechanisms and associations are presented graphically using methodology previously defined as a causal model with design, i.e. a functional causal model extended with the study design. This tool forces the statistician to make the study design and the missing-data mechanism explicit…
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 …