title: LongCriSP: a test for bump hunting in longitudinal data.
abstract: We propose an extension of the Harezlak and Heckman (J. Comput. Graph. Statist. 2001; 10(4): 713-729) test for detecting local extrema to the longitudinal data setting. We use penalized spline regression techniques (Statist. Sci. 1996; 11:89-102) to provide a computationally efficient method of testing for relatively large data sets. We estimate the p-values of our test, LongCriSP, with a smoothed bootstrap. Our simulation studies indicate that the test is generally conservative and has power exceeding 70 per cent at the alpha = 0.1 nominal level in most considered settings. Finally, we apply our testing procedure to the longitudinal measurements of body mass index of former prisoners of war in Vietnam and conclude that the mean population curve exhibits non-monotone behaviour.
authors.affiliation: Department of Biostatistics, Harvard University, Boston, MA 02115, USA. jharezla@hsph.harvard.edu
authors.forename: Jaroslaw
authors.initials: J
authors.lastname: Harezlak
authors.forename: Elena
authors.initials: E
authors.lastname: Naumova
authors.forename: Nan M
authors.initials: NM
authors.lastname: Laird
mesh_terms: D015992:Body Mass Index; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010808:Physical Examination / Q000706:statistics & numerical data*; D011329:Prisoners; D014481:United States