Results 61 to 70 of about 1,808,699 (310)
Principled Missing Data Treatments
We review a number of issues regarding missing data treatments for intervention and prevention researchers. Many of the common missing data practices in prevention research are still, unfortunately, ill-advised (e.g., use of listwise and pairwise deletion, insufficient use of auxiliary variables).
Lang, Kyle, Little, Todd D.
openaire +4 more sources
ABSTRACT Background Neuromyelitis optica spectrum disorder (NMOSD) is a relapsing autoimmune disease of the central nervous system. High‐dose intravenous methylprednisolone (IVMP) is the standard first‐line therapy for acute attacks, although some patients remain refractory.
Wataru Horiguchi +5 more
wiley +1 more source
ABSTRACT Introduction Bloodstream infections due to repeated vascular access (VA) puncture and circuit connections remain major concerns in hemodialysis. Therefore, we examined current practices for glove, disinfectant, and personal protective equipment (PPE) use according to VA type in national university hospitals in Japan.
Aiko Yamada +6 more
wiley +1 more source
Ton J. Cleophas, Aeilko H. Zwinderman
openaire +3 more sources
Informative missingness in electronic health record systems: the curse of knowing
Electronic health records provide a potentially valuable data source of information for developing clinical prediction models. However, missing data are common in routinely collected health data and often missingness is informative.
Rolf H. H. Groenwold
doaj +1 more source
A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024
ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho +7 more
wiley +1 more source
In this study, we suggest an optimal imputation strategy for the elevated estimation of the population mean of the primary variable utilizing the known auxiliary parameters for the missing observations.
Subhash Kumar Yadav +2 more
doaj +1 more source
An important limitation in fisheries research using time series is the presence of missing data. An inadequate handling of these data can negatively impact the results of statistical analyses, leading to erroneous decision-making. A potential solution to
Julian Gomez +2 more
doaj +1 more source
ABSTRACT Background Therapeutic apheresis (TA) is an established treatment modality for hematologic, neurologic, and immunologic disorders, yet access remains severely limited in sub‐Saharan Africa. Donor apheresis, including platelet apheresis collection from healthy donors, represents an important complementary modality supporting blood product ...
Nosa Bazuaye +33 more
wiley +1 more source
Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms [PDF]
The paper extends existing models for multilevel multivariate data with mixed response types to handle quite general types and patterns of missing data values in a wide range of multilevel generalized linear models.
Browne, William J +8 more
core +1 more source

