[HTML][HTML] Missing data in clinical research: a tutorial on multiple imputation
Missing data is a common occurrence in clinical research. Missing data occurs when the
value of the variables of interest are not measured or recorded for all subjects in the sample …
value of the variables of interest are not measured or recorded for all subjects in the sample …
Effect of intra-articular platelet-rich plasma vs placebo injection on pain and medial tibial cartilage volume in patients with knee osteoarthritis: the RESTORE …
Importance Most clinical guidelines do not recommend platelet-rich plasma (PRP) for knee
osteoarthritis (OA) because of lack of high-quality evidence on efficacy for symptoms and …
osteoarthritis (OA) because of lack of high-quality evidence on efficacy for symptoms and …
[HTML][HTML] OpenSAFELY: factors associated with COVID-19 death in 17 million patients
OpenSAFELY: factors associated with COVID-19 death in 17 million patients - PMC Back to
Top Skip to main content NIH NLM Logo Access keys NCBI Homepage MyNCBI Homepage …
Top Skip to main content NIH NLM Logo Access keys NCBI Homepage MyNCBI Homepage …
Factors associated with COVID-19-related death using OpenSAFELY
Abstract Coronavirus disease 2019 (COVID-19) has rapidly affected mortality worldwide.
There is unprecedented urgency to understand who is most at risk of severe outcomes, and …
There is unprecedented urgency to understand who is most at risk of severe outcomes, and …
[HTML][HTML] Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete
This study aims to provide an efficient and accurate machine learning (ML) approach for
predicting the creep behavior of concrete. Three ensemble machine learning (EML) models …
predicting the creep behavior of concrete. Three ensemble machine learning (EML) models …
Accounting for missing data in statistical analyses: multiple imputation is not always the answer
RA Hughes, J Heron, JAC Sterne… - International journal of …, 2019 - academic.oup.com
Background Missing data are unavoidable in epidemiological research, potentially leading
to bias and loss of precision. Multiple imputation (MI) is widely advocated as an …
to bias and loss of precision. Multiple imputation (MI) is widely advocated as an …
Missing data and multiple imputation in clinical epidemiological research
AB Pedersen, EM Mikkelsen, D Cronin-Fenton… - Clinical …, 2017 - Taylor & Francis
Missing data are ubiquitous in clinical epidemiological research. Individuals with missing
data may differ from those with no missing data in terms of the outcome of interest and …
data may differ from those with no missing data in terms of the outcome of interest and …
[HTML][HTML] The role of children in the spread of COVID-19: Using household data from Bnei Brak, Israel, to estimate the relative susceptibility and infectivity of children
One of the significant unanswered questions about COVID-19 epidemiology relates to the
role of children in transmission. This study uses data on infections within households in …
role of children in transmission. This study uses data on infections within households in …
missMDA: a package for handling missing values in multivariate data analysis
We present the R package missMDA which performs principal component methods on
incomplete data sets, aiming to obtain scores, loadings and graphical representations …
incomplete data sets, aiming to obtain scores, loadings and graphical representations …
Effect of aspirin vs enoxaparin on symptomatic venous thromboembolism in patients undergoing hip or knee arthroplasty: the CRISTAL randomized trial
Importance There remains a lack of randomized trials investigating aspirin monotherapy for
symptomatic venous thromboembolism (VTE) prophylaxis following total hip arthroplasty …
symptomatic venous thromboembolism (VTE) prophylaxis following total hip arthroplasty …