Results 161 to 170 of about 3,279,698 (336)

Correction: Publication Bias in Recent Meta-Analyses

open access: yesPLoS ONE, 2013
Michal Kicinski
doaj   +3 more sources

Correction: Publication Bias in Recent Meta-Analyses

open access: yesPLoS ONE, 2014
Michal Kicinski
doaj   +3 more sources

Publication bias

open access: yesJournal of the American College of Cardiology, 1994
openaire   +4 more sources

Screening for Social Determinants of Health in Patients with Systemic Lupus Erythematosus: A Point‐of‐Care Feasibility Study

open access: yesArthritis Care &Research, Accepted Article.
Objectives Social determinants of health (SDoH) can impact outcomes but are not routinely screened for in US outpatient rheumatology clinics. This study determined the feasibility of routine point‐of‐care SDoH screening among patients with systemic lupus erythematosus (SLE), and associated barriers and facilitators at the physician, care team, and ...
S. Sam Lim   +11 more
wiley   +1 more source

Editorial: Minimizing publication bias

open access: yesAustralasian Orthodontic Journal, 2003
Harkness Michael
doaj   +1 more source

Agreement of administrative pharmacy dispensing with self‐reported use of oral prednisone in US Veterans with rheumatoid arthritis

open access: yesArthritis Care &Research, Accepted Article.
Objective Administrative claims are used to evaluate oral glucocorticoid use in rheumatoid arthritis (RA), despite limited evidence to support accuracy. We aimed to evaluate the performance of claims‐based algorithms for glucocorticoid use compared to self‐report in an RA population.
Beth I. Wallace   +16 more
wiley   +1 more source

Publication bias is the consequence of a lack of diversity, equity, and inclusion. [PDF]

open access: yesJ Vasc Surg, 2021
Rouan J   +3 more
europepmc   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez   +2 more
wiley   +1 more source

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