Results 121 to 130 of about 24,713,244 (334)

Handling missing data in research

Perspectives in Clinical Research
Missing data are an inevitable part of research and lead to a decrease in the size of the analyzable population, and biased and imprecise estimates. In this article, we discuss the types of missing data, methods to handle missing data and suggest ways in
Priya Ranganathan, Sally Hunsberger
doaj   +1 more source

A Comparative Study on Missing Value Imputation Techniques in Machine Learning [PDF]

SHS Web of Conferences
Handling missing values is a crucial step in data preprocessing, as incomplete data can significantly impact model performance and overall data integrity.
Meng Haoyu
doaj   +1 more source

Income Imputation and the Analysis of Expenditure Data in the Consumer Expenditure Survey [PDF]

The Consumer Expenditure (CE) Survey began imputing income in its 2004 data. Imputation predicts income for households that reported receiving income but failed to report a specific value.
Jonathan Fisher
core  

Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial

Arthritis Care &Research, EarlyView.
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham, Thea Senger‐Carpenter, Jocelyn Zuckerman, Michelle Adler, Mallet R. Reid, Ashley Danguecan, Luana Flores Pereira, Sarah I. Mossad, Samantha L. Ely, Khalid Abulaban, Elizabeth A. Kessler, Natalie Rosenwasser, Tamar B. Rubinstein, Ekemini A. Ogbu, Emily A. Smitherman, Alaina Miller, Taylor Abounader, Elizabeth Ross, Livie Timmerman, Dhriti Sharma, Jennifer N. Stinson, Stacy Allen, Kabita Nanda, Tala El Tal, Deborah M. Levy, Linda T. Hiraki, Hermine I. Brunner, Mathew Reeves, Steven J. Pierce, Andrea Knight   +29 more
wiley   +1 more source

An Imputation Method for Missing Data Based on an Extreme Learning Machine Auto-Encoder

IEEE Access, 2018
This paper proposes an imputation method for missing data based on an extreme learning machine auto-encoder (ELM-AE). The imputation chooses a set of plausible values determined by ELM-AE and then substitutes the average of these plausible values for the
Cheng-Bo Lu, Ying Mei
doaj   +1 more source

Mycophenolate Mofetil Treatment Reduces the Risk of Treatment Escalation Due to Vascular Complications in Limited Cutaneous Systemic Sclerosis: Emulation of a Target Trial From the Italian Rheumatology Society SPRING Registry

Arthritis Care &Research, EarlyView.
Objective Mycophenolate mofetil (MMF) use in limited cutaneous systemic sclerosis (lcSSc) is relatively uncommon because of the lower fibrotic burden and the predominance of vascular complications. In vitro observations and clinical data from transplanted patients suggest a protective effect of MMF on endothelial function.
Enrico De Lorenzis, Gerlando Natalello, Rossella De Angelis, Lucrezia Verardi, Dilia Giuggioli, Gianluigi Bajocchi, Lorenzo Dagna, Silvia Bellando‐Randone, Giovanni Zanframundo, Rosario Foti, Fabio Cacciapaglia, Giovanna Cuomo, Alarico Ariani, Edoardo Rosato, Gemma Lepri, Francesco Girelli, Valeria Riccieri, Elisabetta Zanatta, Ilaria Cavazzana, Francesca Ingegnoli, Maria De Santis, Giuseppe Murdaca, Giuseppina Abignano, Giorgio Pettiti, Alessandra Della Rossa, Maurizio Caminiti, Annamaria Iuliano, Giovanni Ciano, Lorenzo Beretta, Gianluca Bagnato, Ennio Lubrano, Maria Ilenia De Andres, Alessandro Giollo, Cosimo Bruni, Martina Orlandi, Marco Fornaro, Marta Saracco, Cecilia Agnes, Pier Giacomo Cerasuolo, Gabriella Alonzi, Edoardo Cipolletta, Federica Lumetti, Amelia Spinella, Luca Magnani, Corrado Campochiaro, Giacomo De Luca, Veronica Codullo, Elisa Visalli, Carlo Iandoli, Antonietta Gigante, Greta Pellegrino, Erika Pigatto, Maria‐Grazia Lazzaroni, Franco Franceschini, Elena Generali, Gianna Mennillo, Simone Barsotti, Giuseppa Pagano Mariano, Federica Furini, Licia Vultaggio, Simone Parisi, Clara Lisa Peroni, Gerolamo Bianchi, Enrico Fusaro, Gian Domenico Sebastiani, Marcello Govoni, Salvatore D'Angelo, Franco Cozzi, Fabrizio Conti, Serena Guiducci, Andrea Doria, Carlo Salvarani, Florenzo Iannone, Maria Antonietta D'Agostino, Clodoveo Ferri, Marco Matucci Cerinic, Silvia Laura Bosello, on behalf of the SPRING Italian Registry Collaborators   +77 more
wiley   +1 more source

Imputation estimators for unnormalized models with missing data [PDF]

, 2019
Several statistical models are given in the form of unnormalized densities, and calculation of the normalization constant is intractable. We propose estimation methods for such unnormalized models with missing data.
Kim, Jae Kwang, Kim, Jae Kwang, Matsuda, Takeru, Uehara, Masatoshi   +3 more
core   +3 more sources

Addressing Economic Insecurities Can Improve Patient‐Reported Outcomes in Lupus

Arthritis Care &Research, EarlyView.
Objective Economic insecurities, such as food, housing, transportation, and financial challenges, are modifiable risk factors and influence patient‐reported outcomes (PROs) in systemic lupus erythematosus (SLE). We examined the following: (1) associations between economic insecurities and PROs, and (2) the impact of screening and addressing economic ...
Jay Patel, Tripti Singh, Meredith Ingersoll, Shelby Gomez, Amanda Weber, Sarah E. Panzer, Sancia Ferguson, Christie M. Bartels, Shivani Garg   +8 more
wiley   +1 more source

Improving the performance of Bayesian networks in non-ignorable missing data imputation

Kuwait Journal of Science, 2013
The issue of missing data may arise for researchers who deal with data gathering problems. Bayesian networks are one of the proposed methods that have been recently used in missing data imputation.
P. NILOOFAR, M. GANJALI, AND M.R. FARID ROHANI   +2 more
doaj  

Multiple Imputation for Longitudinal Data: A Tutorial

Statistics in Medicine
ABSTRACTLongitudinal studies are frequently used in medical research and involve collecting repeated measures on individuals over time. Observations from the same individual are invariably correlated and thus an analytic approach that accounts for this clustering by individual is required.
Rushani Wijesuriya, Margarita Moreno‐Betancur, John B. Carlin, Ian R. White, Matteo Quartagno, Katherine J. Lee   +5 more
openaire   +3 more sources