Article

Bayesian methods for modelling non-random missing data mechanisms in longitudinal studies

2010-01-01

Abstract excerpt

In longitudinal studies, data are collected on a group of individuals over a period of time, and inevitably this data will contain missing values. Assuming that this missingness follows convenient `random- like' patterns may not be realistic, so there is much interest in methods for analysing incomplete longitudinal data which allow the incorporation of more realistic assumptions about the missing data mechanism....

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 45106498-d955-5d7b-a05f-8967597db9f7
DOI: 10.25560/5498

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 11 closest

Bayesian methods for modelling non-random missing data mechanisms in longitudinal studiesDOI 10.25560/5498Read

Methods for the analysis of incomplete longitudinal dataSemantic proximity Read

Dealing with Missing Data in Real-World Data: A Scoping Review of Simulation StudiesSemantic proximity Read

A Comparative Study of Methods for Handling Missing Data in Longitudinal Data with Implications for Causal InferenceSemantic proximity Read

Multiple Imputation Approaches for Missing Time-to-Event Outcomes with Informative Censoring: Practical Considerations from a Simulation Study Based on Real DataSemantic proximity Read

Bias due to missing exposure data using complete-case analysis in the proportional hazards regression model.Semantic proximity Read

Characterizing and Managing Missing Structured Data in Electronic Health RecordsSemantic proximity Read

Missing phenotype data imputation in pedigree data analysis.Semantic proximity Read

Data Missingness in Digital Phenotyping: Implications for Clinical Inference and Decision-MakingSemantic proximity Read

Dealing with partially observed covariates in propensity score analysis of observational dataSemantic proximity Read

Using missing data methods in genetic studies with missing mutation status.Semantic proximity Read

Application of Propensity Score Methods to Address Missing Data in a Trial on the Effect of Energy Protein Supplementation Among Pulmonary TB-HIV Patients in Mwanza, TanzaniaSemantic proximity Read