Sensitivity and specificity: Difference between revisions

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In [[statistics]], the '''Ramsey Regression Equation Specification Error Test (RESET) test''' (Ramsey, 1969) is a general [[specification (regression)|specification]] test for the [[linear regression]] model. More specifically, it tests whether non-linear combinations of the fitted values help explain the [[response variable]]. The intuition behind the test is that if non-linear combinations of the [[explanatory variable]]s have any power in explaining the response variable, the model is mis-specified.  
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==Technical summary==
Consider the model
 
: <math>\hat{y}=E\{y|x\}=\beta x.</math>  
 
The Ramsey test then tests whether <math>(\beta x)^2, (\beta x)^3...,(\beta x)^k</math> has any power in explaining <math>y</math>. This is executed by estimating the following [[linear regression]]
 
: <math>y=\alpha x + \gamma_1\hat{y}^2+...+\gamma_{k-1}\hat{y}^k+\epsilon</math>,
 
and then testing, by a means of a [[F-test]] whether <math>\gamma_1~</math> through <math>~\gamma_{k-1}</math> are zero. If the null-hypothesis that all <math>\gamma~</math> coefficients are zero is rejected, then the model suffers from mis-specification.
 
==References==
* Ramsey, J.B. (1969) "Tests for Specification Errors in Classical Linear Least Squares Regression Analysis", ''[[Journal of the Royal Statistical Society]], Series B.'', 31(2), 350&ndash;371. {{JSTOR|2984219}}
 
*Thursby, J.G., Schmidt, P. (1977) "Some Properties of Tests for Specification Error in a Linear Regression Model", ''[[Journal of the American Statistical Association]]'', 72, 635&ndash;641. {{JSTOR|2286231}}
 
*Murteira, Bento. (2008) ''Introdução à Estatística'', McGraw Hill. 
 
*Wooldridge, Jeffrey M. (2006) ''Introductory Econometrics - A Modern Approach'', Thomson South-Western, International Student Edition.
 
[[Category:Statistical tests]]
[[Category:Regression diagnostics]]

Revision as of 03:49, 23 February 2014

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