The long term goals of this research program are to develop statistical methodology for the analysis and biomedical data that is based on non- and semi-parametric curve estimation theory, and to develop tools for parametric model building. Computer simulation studies will be executed to verify that the asymptotic theory developed is useful for interference with sample sizes typically encountered in biomedical data sets described in this proposal. The following problems will be studied during the proposed funding period: 1. Estimation in the Additive Model for Non-parametric Regression: An algorithm is proposed here for fitting the additive model in multiple regression. Consistency of the estimators should hold without restricting dependencies among the co-variates. 2. Non-parametric Regression Analysis of Multi-variate Longitudinal Data. a. This research project is motivated by a data set that was obtained from Phase I study to determine the safety of Droloxifene in patients with advanced metastatic breast cancer. The levels of several hormones were monitored at the time of entry to the study and repeatedly thereafter. This is a continuation of research reported in Staniswalis and Lee (1997). The smooth non-parametric estimators of the covariance function will be studied further. Development of methods for a canonical correlation analysis for random curves is proposed to characterize associations among the four different hormones over time, and to determine if there is a dependence on the dose of Droloxifene. b. Redundancy analysis is used when it is of interest to predict one set of variables with a predictor constructed from another set of variables. For this specific aim, this standard multi-variate methodology of redundancy analysis for vectors will be extended to understand how a collection of random curves could be used to best predict another collection of random curves.

Project Start
1999-06-01
Project End
2000-05-31
Budget Start
1998-10-01
Budget End
1999-09-30
Support Year
29
Fiscal Year
1999
Total Cost
Indirect Cost
Name
University of Texas El Paso
Department
Type
DUNS #
City
El Paso
State
TX
Country
United States
Zip Code
79968
Rocha-Gutiérrez, Beatriz A; Lee, Wen-Yee; Shane Walker, W (2016) Mass balance and mass loading of polybrominated diphenyl ethers (PBDEs) in a tertiary wastewater treatment plant using SBSE-TD-GC/MS. Water Sci Technol 73:302-8
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Rico-Martínez, Roberto; Walsh, Elizabeth J (2013) Sexual Reproductive Biology of a Colonial Rotifer Sinantherina socialis (Rotifera: Monogononta): Do mating strategies vary between colonial and solitary rotifer species? Mar Freshw Behav Physiol 46:419-430
Jin, Seoweon; Staniswalis, Joan G; Mallawaarachchi, Indika (2013) Principal Differential Analysis with a Continuous Covariate: Low Dimensional Approximations for Functional Data. J Stat Comput Simul 83:
Dagda, Ruben K; Gasanov, Sardar; De La Oiii, Ysidro et al. (2013) Genetic Basis for Variation of Metalloproteinase-Associated Biochemical Activity in Venom of the Mojave Rattlesnake (Crotalus scutulatus scutulatus). Biochem Res Int 2013:251474

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