Results 31 to 40 of about 293,806 (294)
Attribute frequency and misclassification bias
Journal of Chronic Diseases, 1987 Allowances for potential misclassification bias were performed for three epidemiologic studies. Although the error rates were assumed to be identical for the three studies, there were differences in the degree and even in the direction of the bias.
J M, Sosenko, L B, Gardner
openaire +2 more sources
Aging and Cancer, EarlyView.This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel +4 more
wiley +1 more source
The arithmetic dilemma when defining thinness, overweight and obesity in stunted populations
Human Biology and Public Health, 2022 Background: Critical cut-off values of BMI-for-age z-scores (BAZ) are used to define “thinness”, “overweight” and “obesity”, but the validity of these cut-off values needs to be questioned in populations that are shorter or taller than the reference. We
Michael Hermanussen +3 more
doaj +1 more source
The Problem of Worker Misclassification [PDF]
, 2010 Employee misclassification is a significant problem that continues to plague the labor market. Unscrupulous and unknowing employers alike are costing individual workers and society tremendously.
Parisi, Ryan
core +1 more source
, 2016 Automated data-driven decision making systems are increasingly being used to assist, or even replace humans in many settings. These systems function by learning from historical decisions, often taken by humans.
Barocas S. +12 more
core +1 more source
Tracking Motor Progression and Device‐Aided Therapy Eligibility in Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To characterise the progression of motor symptoms and identify eligibility for device‐aided therapies in Parkinson's disease, using both the 5‐2‐1 criteria and a refined clinical definition, while examining differences across genetic subgroups.
David Ledingham +7 more
wiley +1 more source
Techniques to Deal with Off-Diagonal Elements in Confusion Matrices
Mathematics, 2021 Confusion matrices are numerical structures that deal with the distribution of errors between different classes or categories in a classification process. From a quality perspective, it is of interest to know if the confusion between the true class A and
Inmaculada Barranco-Chamorro +1 more
doaj +1 more source
The risk of misclassifying subjects within principal component based asset index. [PDF]
, 2014 The asset index is often used as a measure of socioeconomic status in empirical research as an explanatory variable or to control confounding. Principal component analysis (PCA) is frequently used to create the asset index.
Abedin, Jaynal +4 more
core +2 more sources
Hospital Readmission After Traumatic Brain Injury Hospitalization in Community‐Dwelling Older Adults
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To examine the risk of hospital readmission after an index hospitalization for TBI in older adults. Methods Using data from the Atherosclerosis Risk in Communities (ARIC) study, we used propensity score matching of individuals with an index TBI‐related hospitalization to individuals with (1) non‐TBI hospitalizations (primary analysis)
Rachel Thomas +7 more
wiley +1 more source
Wald Confidence Intervals for a Single Poisson Parameter and Binomial Misclassification Parameter When the Data is Subject to Misclassification [PDF]
, 2018 This thesis is based on a Poisson model that uses both error-free data and error-prone data subject to misclassification in the form of false-negative and false-positive counts.
Poddiwala Hewage, Nishantha Janith Chandrasena
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