Results 221 to 230 of about 3,364,346 (276)

Common misconceptions held by health researchers when interpreting linear regression assumptions, a cross-sectional study. [PDF]

PLoS One
Jones L, Barnett A, Vagenas D.
europepmc   +1 more source

Comparison of Artificial Neural Network and Multiple Linear Regression to Predict Cadmium Concentration in Rice: A Field Study in Guangxi, China. [PDF]

Toxics
Zhao J, Zheng F, Yu B, Qin G, Meng S, Qiu Y, He B.   +6 more
europepmc   +1 more source

A hybrid approach for forecasting peak expiratory flow rate in asthma patients using combined linear regression and random forest model. [PDF]

PLoS One
Alkobaisi S, Bae WD, Safdar MF, Safdar MF, Abu Ali NA, Kim S, Park CS, Nowak RM.   +7 more
europepmc   +1 more source

Linear regression analysis for complete blood count parameters during radiotherapy. [PDF]

Strahlenther Onkol
Berpan A, Janhom N.
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Linearized Ridge Regression Estimator in Linear Regression

Communications in Statistics - Theory and Methods, 2011
In this article, we aim to study the linearized ridge regression (LRR) estimator in a linear regression model motivated by the work of Liu (1993). The LRR estimator and the two types of generalized Liu estimators are investigated under the PRESS criterion.
Xu-Qing Liu, Feng Gao
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Understanding Linear Regression

PM&R, 2013
Multivariate regression is a powerful statistical technique that allows researchers to explore multiple predictors simultaneously, to adjust for confounding, to test for interactions, and to improve predictions. Commonly used regression models include linear regression, logistic regression, and Cox regression.
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Regression: simple linear

International Journal of Injury Control and Safety Promotion, 2018
Regression is a statistical term used for describing models that estimate the relationships among variables.
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Regression: multiple linear

International Journal of Injury Control and Safety Promotion, 2018
Simple linear regression models study the relationship between a single continuous dependent variable Y and one independent variable X (Bangdiwala, 2018).
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