Results 31 to 40 of about 300,687 (184)
Sequential Regression: A Neodescriptive Approach to Multicollinearity [PDF]
Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence ...
Norman Fickel
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Decreasing Multicollinearity [PDF]
Sociological Methods & Research, 1979 When the multicollinearity among the independent variables in a regression model is due to the high correlations of a multiplicative function with its constituent variables, the multicollinearity can be greatly reduced by centering these variables around minimizing constants before forming the multiplicative function.
Kent W. Smith, M.S. Sasaki
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On Testing Sample Selection Bias under the Multicollinearity Problem [PDF]
, 2006 This paper examines and compares the finite sample performance of the existing tests for sample selection bias, especially under the multi-collinearity problem pointed out by Nawata (1993).
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Journal of Epidemiology and Global Health, 2020 Although malaria burden has declined globally following scale up of intervention, the disease has remained a leading cause of hospitalization and deaths among children aged under-5 years in Nigeria.
Chigozie Louisa Jane Ugwu +1 more
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E-Jurnal Matematika, 2014 Multiple linear regression analysis with a lot of independent variable always makes many problems because there is a relationship between two or more independent variables.
NI WAYAN YULIANI +2 more
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El problema de un tamaño muestral pequeño en la regresión lineal: Micronumerosidad
Rect@, 2016 : The econometrician Arthur Goldberg introduced the notion of micronumerosity motivating that classical Econometrics textbooks used to explain the problem of multicollinearity but nothing is explain about the analogous problem of estimating using an ...
Salmeron, Román, Blanco, Víctor
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MathematicsOutliers are a common problem in applied statistics, together with multicollinearity. In this paper, robust Liu estimators are introduced into a partially linear model to combat the presence of multicollinearity and outlier challenges when the error ...
Waleed B. Altukhaes +2 more
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Multicollinearity: Effects, Symptoms, and Remedies [PDF]
Journal of the Northeastern Agricultural Economics Council, 1978 Multicollinearity is one of several problems confronting researchers using regression analysis. This paper examines the regression model when the assumption of independence among the independent variables is violated. The basic properties of the least squares approach are examined, the concept of multicollinearity and its consequences on the least ...
Willis, Cleve E., Perlack, Robert D.
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Mitigating Multicollinearity in Regression: A Study on Improved Ridge Estimators
MathematicsMulticollinearity, a critical issue in regression analysis that can severely compromise the stability and accuracy of parameter estimates, arises when two or more variables exhibit correlation with each other.
Nadeem Akhtar +2 more
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Acta Agronómica, 2009 Este trabalho objetivou avaliar a necessidade de realizar análise de trilha individualizada para tomates tipo Salada (L. esculentum) e Cereja (L. esculentum var.
Fábio Moreira Sobreira +5 more
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