[HTML][HTML] Predictors of ASDAS-CRP inactive disease in axial spondyloarthritis during treatment with TNF-inhibitors: Data from the EuroSpA collaboration
LM Ørnbjerg, L Linde, S Georgiadis… - Seminars in arthritis and …, 2022 - Elsevier
Objectives In patients with axial spondyloarthritis (axSpA) initiating their first tumor necrosis
factor alpha-inhibitor (TNFi), we aimed to identify common baseline predictors of Ankylosing …
factor alpha-inhibitor (TNFi), we aimed to identify common baseline predictors of Ankylosing …
Evaluation of four multiple imputation methods for handling missing binary outcome data in the presence of an interaction between a dummy and a continuous …
Multiple imputation by chained equations (MICE) is the most common method for imputing
missing data. In the MICE algorithm, imputation can be performed using a variety of …
missing data. In the MICE algorithm, imputation can be performed using a variety of …
School racial composition, effect modification by caring teacher/staff presence, and mid/late-life depressive symptoms: findings from the Study of Healthy Aging among …
For Black students in the United States, attending schools with a higher proportion of White
students is associated with worse mental and physical health outcomes in …
students is associated with worse mental and physical health outcomes in …
[HTML][HTML] Multiple imputation using chained equations for missing data in survival models: applied to multidrug-resistant tuberculosis and HIV data
SV Mbona, H Mwambi, S Ramroop - Journal of Public Health in …, 2023 - ncbi.nlm.nih.gov
Background. Missing data are a prevalent problem in almost all types of data analyses, such
as survival data analysis. Objective. To evaluate the performance of multivariable imputation …
as survival data analysis. Objective. To evaluate the performance of multivariable imputation …
[HTML][HTML] Comparing methods for handling missing cost and quality of life data in the Early Endovenous Ablation in Venous Ulceration trial
Objectives This study compares methods for handling missing data to conduct cost-
effectiveness analysis in the context of a clinical study. Methods Patients in the Early …
effectiveness analysis in the context of a clinical study. Methods Patients in the Early …
Multifunctional optimized group method data handling for software effort estimation
SH Arbain - 2022 - eprints.uthm.edu.my
Nowadays, the trend of significant effort estimations is in demand. Due to its popularity, the
stakeholder needs effective and efficient software development processes with the best …
stakeholder needs effective and efficient software development processes with the best …
Predictors of ASDAS Inactive Disease in Axial Spondyloarthritis During Treatment with TNF-Inhibitors: Data from the Eurospa Collaboration
LM Ørnbjerg, L Linde, S Georgiadis, SH Rasmussen… - papers.ssrn.com
Objectives: In patients with axial spondyloarthritis (axSpA) initiating their first tumour
necrosis factor alpha-inhibitor (TNFi), we aimed to identify common baseline predictors of …
necrosis factor alpha-inhibitor (TNFi), we aimed to identify common baseline predictors of …
[PDF][PDF] Research Article Evaluation of Four Multiple Imputation Methods for Handling Missing Binary Outcome Data in the Presence of an Interaction between a Dummy …
Multiple imputation by chained equations (MICE) is the most common method for imputing
missing data. In the MICE algorithm, imputation can be performed using a variety of …
missing data. In the MICE algorithm, imputation can be performed using a variety of …