Results 51 to 60 of about 1,083,294 (265)

Methods to Handle Incomplete Data

MAMC Journal of Medical Sciences, 2020
Context: The major question for data analysis is determining the appropriate analytic approach in the presence of incomplete observations. The most common solution to handle missing data in a data set is imputation, where missing values are estimated and
Vinny Johny, Mariamma Philip, Swathi Augustine   +2 more
doaj   +1 more source

A comparison of incomplete-data methods for categorical data [PDF]

Statistical Methods in Medical Research, 2012
We studied four methods for handling incomplete categorical data in statistical modeling: (1) maximum likelihood estimation of the statistical model with incomplete data, (2) multiple imputation using a loglinear model, (3) multiple imputation using a latent class model, (4) and multivariate imputation by chained equations.
van der Palm, D.W., van der Ark, L.A., Vermunt, J.K.   +2 more
openaire   +3 more sources

Chemotherapy for Spinal Cord Intramedullary Pediatric Low‐Grade Glioma—A Systematic Literature Review

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric intramedullary low‐grade gliomas (PIMLGGs) are rare neoplasms that present unique clinical and management challenges. Although surgery remains the primary tool for tissue diagnosis and decompression, complete gross‐total resection is frequently unfeasible due to the infiltrative nature of these lesions.
Olga M. Sergeenko, Segev Gabay, Jonathan Roth, Amit Ringel, Rina Dvir, Shlomi Constantini   +5 more
wiley   +1 more source

Bone and Soft Tissue Neoplasms in Infants Versus Older Children: A Report From the Cancer in Young People in Canada Program

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background and Aims Infant bone and soft tissue neoplasms present distinct clinical challenges and lack large‐scale data to inform treatment decisions. This study aims to characterize bone and soft tissue neoplasms in infants in Canada and to compare their outcomes with those of older pediatric patients.
Samuel Sassine, Hallie Coltin, Maria Kondyli, Monia Marzouki, Nicolas Prud'homme, Nida Usmani, Rebecca J. Deyell, Lesleigh Abbott, Tony H. Truong, Sapna Oberoi, Ketan Kulkarni, Josée Brossard, Lynette Bowes, Paul Gibson, Sarah McKillop, Roona Sinha, Lillian Sung, Catherine Vezina, Laura Wheaton, Alexandra P. Zorzi, Marie‐Claude Pelland‐Marcotte, Thai Hoa Tran   +21 more
wiley   +1 more source

An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis

Entropy, 2019
Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables.
Shinpei Imori, Hidetoshi Shimodaira
doaj   +1 more source

Multivariate Tests with Incomplete Data

The Annals of Statistics, 1983
In the context of a normal model, testing problems with missing data are considered. Tests on means are treated when independent extra data on the first $p_1$ variates of $p$ variates is available in addition to complete data. For testing that the mean of the first $p_1$ variates is zero, the LRT is UMP invariant, but for testing that the whole mean is
Eaton, Morris, Kariya, Takeaki
openaire   +2 more sources

Effectiveness of Resistance Intradialytic Exercise Compared to Aerobic Intradialytic Exercise for Patients With Chronic Kidney Disease: A Randomized Controlled Clinical Trial

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida, Gisela Cristiane Miyamoto, Daniel da Costa Torres, Ian Setubal Reis Chaves, Jonas do Carmo Paschoalin, Braúlio Lima Nascimento, Luciana Dias Chiavegato   +6 more
wiley   +1 more source

Regression SVM for Incomplete Data

Schedae Informaticae, 2017
The use of machine learning methods in the case of incomplete data is an important task in many scientific fields, like medicine, biology, or face recognition. Typically, missing values are substituted with artificial values that are estimated from the known samples, and the classical machine learning algorithms are applied.
Struski, Łukasz, Śmieja, Marek, Zieliński, Bartosz, Tabor, Jacek   +3 more
openaire   +3 more sources

Organizing the interface—Plasma membrane architecture and receptor dynamics in virus‐cell interactions

FEBS Letters, EarlyView.
Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley   +1 more source

Residual tail twisting in ascidian larvae is stabilized by asymmetric myofibrils that resist bilateral symmetry restoration

FEBS Letters, EarlyView.
Ascidian Ciona larvae initially show strong clockwise tail twisting, which is largely corrected during development. However, a small residual twist remains. This study shows that organized helical myofibrils in tail muscles mechanically stabilize this residual asymmetry, preventing complete restoration of bilateral symmetry and revealing how embryos ...
Yuki S. Kogure, Misaki K. Nishio, Satoru Okuda, Kohji Hotta   +3 more
wiley   +1 more source