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Testing the product of slopes in related regressions.
Morrell, Christopher H; Shetty, Veena; Phillips, Terry; Arumugam, Thiruma V; Mattson, Mark P; Wan, Ruiqian.
Afiliación
  • Morrell CH; Mathematics and Statistics Department, Loyola University Maryland, 4501 North Charles St., Baltimore, MD 21210-2699 USA chm@loyola.edu (410)617-2629, ; Laboratory of Cardiovascular Sciences, National Institute on Aging, 5600 Nathan Shock Drive, Baltimore, MD 21224 USA.
  • Shetty V; MedStar Research Institute, Hyattsville, MD USA.
  • Phillips T; Laboratory of Bioengineering & Physical Science, National Institute of Biomedical Imaging & Bioengineering, 9000 Rockville Pike, Bethesda, MD 20892 USA.
  • Arumugam TV; School of Biomedical Sciences, The University of Queensland, Australia.
  • Mattson MP; Laboratory of Neurosciences, National Institute on Aging, 251 Bayview Boulevard, Baltimore, MD 21224 USA.
  • Wan R; Laboratory of Neurosciences, National Institute on Aging, 251 Bayview Boulevard, Baltimore, MD 21224 USA.
Adv Appl Stat ; 36(1): 29-46, 2013 Sep 01.
Article en En | MEDLINE | ID: mdl-25346580
ABSTRACT
A study was conducted of the relationships among neuroprotective factors and cytokines in brain tissue of mice at different ages that were examined on the effect of dietary restriction on protection after experimentally induced brain stroke. It was of interest to assess whether the cross-product of the slopes of pairs of variables vs. age was positive or negative. To accomplish this, the product of the slopes was estimated and tested to determine if it is significantly different from zero. Since the measurements are taken on the same animals, the models used must account for the non-independence of the measurements within animals. A number of approaches are illustrated. First a multivariate multiple regression model is employed. Since we are interested in a nonlinear function of the parameters (the product) the delta method is used to obtain the standard error of the estimate of the product. Second, a linear mixed-effects model is fit that allows for the specification of an appropriate correlation structure among repeated measurements. The delta method is again used to obtain the standard error. Finally, a non-linear mixed-effects approach is taken to fit the linear-mixed-effects model and conduct the test. A simulation study investigates the properties of the procedure.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Adv Appl Stat Año: 2013 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Adv Appl Stat Año: 2013 Tipo del documento: Article