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Relationship between reasons for intermittent missing patient-reported outcomes data and missing data mechanisms
PurposeNon-response (NR) to patient-reported outcome (PRO) questionnaires may cause bias if not handled appropriately. Collecting reasons for NR is...
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On the use of multiple imputation to address data missing by design as well as unintended missing data in case-cohort studies with a binary endpoint
BackgroundCase-cohort studies are conducted within cohort studies, with the defining feature that collection of exposure data is limited to a subset...
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Logical definition-based identification of potential missing concepts in SNOMED CT
BackgroundBiomedical ontologies are representations of biomedical knowledge that provide terms with precisely defined meanings. They play a vital...
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Handling Missing Data in Health Economics and Outcomes Research (HEOR): A Systematic Review and Practical Recommendations
BackgroundMissing data in costs and/or health outcomes and in confounding variables can create bias in the inference of health economics and outcomes...
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Comparison of the effects of imputation methods for missing data in predictive modelling of cohort study datasets
BackgroundMissing data is frequently an inevitable issue in cohort studies and it can adversely affect the study's findings. We assess the...
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Multiple imputation methods for missing multilevel ordinal outcomes
BackgroundMultiple imputation (MI) is an established technique for handling missing data in observational studies. Joint modelling (JM) and fully...
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Dirichlet process mixture models to impute missing predictor data in counterfactual prediction models: an application to predict optimal type 2 diabetes therapy
BackgroundThe handling of missing data is a challenge for inference and regression modelling. A particular challenge is dealing with missing...
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The impact of imputation quality on machine learning classifiers for datasets with missing values
BackgroundClassifying samples in incomplete datasets is a common aim for machine learning practitioners, but is non-trivial. Missing data is found in...
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Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts
Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities....
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The protective effect of CALD identity in the presence of low income on missing teeth of Australian adults over time
Background‘Culturally And Linguistically Diverse (CALD)’ populations have diverse languages, ethnic backgrounds, societal structures and religions....
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A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis
BackgroundMissing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches...
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Missingness in the expanded prostate cancer index short form (EPIC-26) – prevalence, patterns, and explanatory factors
BackgroundResearchers and clinicians using common clinical assessments need to attend to the prevalence of missing data to ensure the validity of the...
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Accommodating heterogeneous missing data patterns for prostate cancer risk prediction
BackgroundWe compared six commonly used logistic regression methods for accommodating missing risk factor data from multiple heterogeneous cohorts,...
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Managing missing items in the Fagerström Test for Nicotine Dependence: a simulation study
BackgroundThe Fagerström Test for Nicotine Dependence (FTND) is frequently used to assess the level of smokers’ nicotine dependence; however, it is...
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Impute the missing data using retrieved dropouts
BackgroundIn the past few decades various methods have been proposed to handle missing data of clinical studies, so as to assess the robustness of...
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Missingness mechanisms and generalizability of patient reported outcome measures in colorectal cancer survivors – assessing the reasonableness of the “missing completely at random” assumption
BackgroundPatient-Reported Outcome Measures (PROM) provide important information, however, missing PROM data threaten the interpretability and...
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The Mediator Role of Fear of Missing Out in the Parent-Adolescent Relationship Quality and Problematic Internet Use
The aim of the research is to examine the direct and indirect relationship between parent-adolescent relationship quality, problematic internet use,...
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Quantifying bias due to missing data in quality of life surveys of advanced-stage cancer patients
PurposeMany studies on cancer patients investigate the impact of treatment on health-related quality of life (QoL). Typically, QoL is measured...
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Non-invasive Hemoglobin Measurement Predictive Analytics with Missing Data and Accuracy Improvement Using Gaussian Process and Functional Regression Model
Recent use of noninvasive and continuous hemoglobin (SpHb) concentration monitor has emerged as an alternative to invasive laboratory-based...
