Results 311 to 320 of about 30,017,606 (359)
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Gini Regression Analysis

International Statistical Review / Revue Internationale de Statistique, 1992
Summary: The method of least squares ranks as one of the most commonly used methods for estimating the relation between a set of variables on the conditional expected value of another variable. Ordinary Least Squares (OLS) relies on several assumptions, which when violated may not yield robust estimates. We pose alternative ways to view this model.
Olkin, Ingram, Yitzhaki, Shlomo
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Factor analysis regression

Statistical Papers, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kosfeld, Reinhold   +1 more
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Nonlinear Regression Analysis of the Joint-Regression Model

Biometrics, 1997
Summary: The joint-regression model for two-way data assumes a linear relation between a continuous response and column effects. Standard methods for fitting the model condition on estimates of the column effects, but including column effects as covariates in the model results in a nonlinear estimation problem.
Ng, Meei Pyng, Grunwald, Gary K.
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Tourism and Economic Growth: A Meta-regression Analysis

Journal of Travel Research, 2019
Numerous studies have focused on delineating the relationship between tourism and economic growth. In this article, we present the results of a rigorous meta-regression analysis based on 545 estimates drawn from 113 studies that empirically tested the ...
R. Nunkoo   +4 more
semanticscholar   +1 more source

Regression-Discontinuity Analysis

2008
The regression discontinuity (RD) data design is a quasi-experimental evaluation design first introduced by Thistlethwaite and Campbell (1960) as an alternative approach to evaluating social programmes. The design is characterized by a treatment assignment or selection rule which involves the use of a known cut-off point with respect to a continuous ...
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Uncertain hypothesis test with application to uncertain regression analysis

Fuzzy Optimization and Decision Making, 2021
Tingqing Ye, Baoding Liu
semanticscholar   +1 more source

Regression and Correlation Analysis

1987
Correlation is a tool for understanding the relationship between two quantities. Regression considers how one quantity is influenced by another. In correlation analysis the two quantities are considered symmetrically: in regression analysis one is supposed dependent on the other, in an unsymmetric way. Extensions to sets of quantities are important.
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Regression Analysis

2018
Abstract This chapter teaches how to use R to conduct regression analysis to answer the question: Does trade promote economic growth? It demonstrates how to specify a statistical model from a theoretical argument, prepare data, estimate and interpret the statistical model, and use the estimated results to make inferences and answer the ...
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