A diagnostic tool for regression analysis of complex survey data

Zilin Wang () and David Bellhouse

Statistical Papers, 2015, vol. 56, issue 4, 1053 pages

Abstract: Although a nonparametric regression model allows us to obtain a graphical display of the relationship between the response variable and the independent variables, the exact form of the regression function is not evident. This weakness can be overcome by a parametric model since the relationship between the dependent and the independent variables is specified mathematically. The object of this paper is to introduce a new graphical approach, called the shift function plot, with which a hypothesis test is constructed to evaluate the goodness-of-fit of a parametric regression model. Under multi-stage stratified sampling schemes, we apply the shift function plots to survey data. Asymptotic properties of the survey estimator of the shift function are established. An empirical example from the 1990 Ontario Health Survey is used to illustrate the application of the shift function. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Nonparametric regression; Regression specification test; Probability sampling; Large data (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s00362-014-0623-5

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