Results 91 to 100 of about 287,343 (334)

Sequential Regression Multiple Imputation for Incomplete Multivariate Data using Markov Chain Monte Carlo [PDF]

This paper discusses the theoretical background to handling missing data in a multivariate context. Earlier methods for dealing with item non-response are reviewed, followed by an examination of some of the more modern methods and, in particular ...
Cally Ardington, Miguel Lacerda, Murray Leibbrandt   +2 more
core   +1 more source

Best Practices for Addressing Missing Data through Multiple Imputation

, 2021
Adrienne D. Woods, Daria Gerasimova, Ben Van Dusen, Jayson Nissen, Sierra A. Bainter, Alex Uzdavines, Pamela Davis‐Kean, Max A. Halvorson, Kevin M. King, Jessica A. R. Logan, Menglin Xu, Martin R. Vasilev, James M. Clay, David Moreau, Keven Joyal‐Desmarais, Rick A. Cruz, Denver M. Y. Brown, Kathleen Schmidt, Mahmoud Medhat Elsherif   +18 more
openalex   +1 more source

Testing a Personalized Approach to Chronic Low Back Pain: A Randomized Controlled Trial in Older Veterans

Arthritis Care &Research, EarlyView.
Objective We aimed to test the efficacy of personalized treatment of older veterans with chronic low back pain (CLBP) delivered by Aging Back Clinics (ABCs) as compared with usual care (UC). Methods Two hundred ninety‐nine veterans aged 65 to 89 with CLBP from three Veterans Affairs (VA) medical centers underwent baseline testing, randomization to ABC ...
Debra K. Weiner, Angela Gentili, Meika A. Fang, Edward Garay, Laura Lawson, Lenore Joseph, Cathy C. Lee, Michelle I. Rossi, Beverly Thorn, Subashan Perera   +9 more
wiley   +1 more source

The Renal Activity Index for Lupus Identifies Active Renal Disease and Treatment Response in Adult Patients With Systemic Lupus Erythematosus and Lupus Nephritis

Arthritis Care &Research, EarlyView.
Objective We evaluated the ability of the Renal Activity Index for Lupus (RAIL) to discriminate active lupus nephritis (LN) in adult patients with active systemic lupus erythematosus (SLE) and differentiate LN treatment response. Methods Urine samples from adults with biopsy‐proven active class III and IV LN from TULIP‐LN (active LN group ...
Hermine I. Brunner, Ellen M. Cody, Prasad Devarajan, Bin Huang, Chen Chen, Dominic Sinibaldi, Madhu Ramaswamy, Jacob Knagenhjelm, Frederick Jones, Philip Z. Brohawn, Raj Tummala, Catharina Lindholm, Wendy I. White   +12 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  

Univariate and multivariate imputation methods evaluation for reconstructing climate time series data: A case study of Mosul station-Iraq

Journal of Agrometeorology
Comprehensive climate time series data is indispensable for monitoring the impacts of climate change. However, observational datasets often suffer from data gaps within their time series, necessitating imputation to ensure dataset integrity for further ...
KHALID QARAGHULI, M. F. MURSHED, M. AZLIN M. SAID, ALI MOKHTAR, IMAN ROUSTA   +4 more
doaj   +1 more source

Addressing Missing Data in Untargeted Metabolomics: Identifying Missingness Type and Evaluating the Impact of Imputation Methods on Experimental Replication [PDF]

, 2021
Trenton J. Davis, Tarek R. Firzli, Emily A. Higgins Keppler, Matt Richardson, Heather D. Bean   +4 more
openalex   +1 more source

Sarilumab in Polyarticular‐Course Juvenile Idiopathic Arthritis: Dose‐Finding and 1‐Year Analysis of a Phase 2b, Open‐Label, Multicenter Study

Arthritis Care &Research, EarlyView.
Objective This study assessed sarilumab in treating patients with polyarticular‐course juvenile idiopathic arthritis (pcJIA). Methods This phase 2b, open‐label study (NCT02776735) consisted of three sequential parts (each with a core‐treatment and extension phase).
Fabrizio De Benedetti, Inmaculada C. Penadés, Irina Nikishina, Ivan Foeldvari, Alberto J. Spindler, Anna Kozlova, Nadina Rubio‐Pérez, Pierre Quartier, Zbigniew Żuber, Raul Barria, Daniel Clemente, Gabriel V. Cornejo, Katherine Marzan, Nancy Liu, Christine Xu, Stephen DiMartino, Angeliki Giannelou, Fei Cao‐Ghoul, Bolanle Akinlade, Lydie Baret‐Cormel   +19 more
wiley   +1 more source

PENDUGAAN DATA HILANG DENGAN MENGGUNAKAN DATA AUGMENTATION

Media Statistika, 2011
Data augmentation is a method for estimating missing data. It is a special case of Gibbs sampling which has two important steps. The first step is imputation or I-step where the missing data is generated based on the conditional distributions for missing
Mesra Nova, Moch. Abdul Mukid
doaj   +1 more source

Improving Missing Data Imputation with Deep Generative Models

, 2019
Datasets with missing values are very common on industry applications, and they can have a negative impact on machine learning models. Recent studies introduced solutions to the problem of imputing missing values based on deep generative models. Previous
Camino, Ramiro D., Hammerschmidt, Christian A., State, Radu   +2 more
core