Describing and Presenting Multivariable Regression Models
نویسندگان
چکیده
منابع مشابه
Quality Reporting of Multivariable Regression Models in Observational Studies
Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly u...
متن کاملComparison of three nonlinear and spline regression models for describing chicken growth curves.
This study compared three non-linear growth models (Richards, Gompertz, and logistic) and the spline linear regression model using BW measurements from an unselected, randombred chicken population. Based on the goodness of fit criteria, the nonlinear models (NLM) fitted the data better than the spline regression model. The four-parameter Richards model was expected to have the best overall fit;...
متن کاملGeneralized Ridge Regression Estimator in Semiparametric Regression Models
In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...
متن کاملQuality of reporting of multivariable logistic regression models in Chinese clinical medical journals
Multivariable logistic regression (MLR) has been increasingly used in Chinese clinical medical research during the past few years. However, few evaluations of the quality of the reporting strategies in these studies are available.To evaluate the reporting quality and model accuracy of MLR used in published work, and related advice for authors, readers, reviewers, and editors.A total of 316 arti...
متن کاملEffectiveness of ensemble machine learning over the conventional multivariable linear regression models
This paper demonstrates the effectiveness of ensemble machine learning algorithms over the conventional multivariable linear regression models including Ordinary Least Squares, Robust Linear Model, and Lasso Model. The ensemble machine learning algorithms include Adaboost, Random-Forest, Bagging, Extremely Randomized Trees, Gradient Boosting, and Extra Trees Regressor. With the progress of open...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Progress in Transplantation
سال: 2020
ISSN: 1526-9248,2164-6708
DOI: 10.1177/1526924820959774