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A Smooth Test of Goodness‐of‐Fit for Growth Curves and Monotonic Nonlinear Regression Models
Author(s) -
Ducharme Gilles R.,
Fontez Bénédicte
Publication year - 2004
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2004.00253.x
Subject(s) - goodness of fit , growth curve (statistics) , monotonic function , test (biology) , nonlinear regression , mathematics , set (abstract data type) , statistics , econometrics , regression analysis , computer science , mathematical analysis , paleontology , biology , programming language
Summary We propose a goodness‐of‐fit test for growth curves based on an adaptation of the data‐driven smooth test paradigm. It is simple to apply and can assess the fit of a model to a set of growth experiences. A simulation study shows that for small samples, the test holds its level. Moreover, its power is found to be generally greater than existing tests. The article concludes by revisiting the long‐standing problem of validating a model for the growth of human stature.