PC program for obtaining orthogonal polynomial regression coefficients for use in longitudinal data analysis
dc.contributor.author | Ten Have, Thomas R. | en_US |
dc.contributor.author | Kowalski, Charles J. | en_US |
dc.contributor.author | Schneiderman, Emet D. | en_US |
dc.date.accessioned | 2006-04-28T17:03:50Z | |
dc.date.available | 2006-04-28T17:03:50Z | |
dc.date.issued | 1992 | en_US |
dc.identifier.citation | Ten Have, Thomas R.; Kowalski, Charles J.; Schneiderman, Emet D. (1992)."PC program for obtaining orthogonal polynomial regression coefficients for use in longitudinal data analysis." American Journal of Human Biology 4(3): 403-416. <http://hdl.handle.net/2027.42/38552> | en_US |
dc.identifier.issn | 1042-0533 | en_US |
dc.identifier.issn | 1520-6300 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/38552 | |
dc.description.abstract | Much of longitudinal data analysis begins with dimensionality reduction, i.e., the replacement of the T observations x 1 , x 2 , …, x T on an individual taken at times t 1 , t 2 , …, t T (not necessarily equally spaced) by a smaller number, P, of parameters which are then used to describe and compare growth processes. We focus on the class of polynomial growth curve models for one-sample data matrices in which the P regression coefficients are estimated by an equation of the form documentclass{article}pagestyle{empty}begin{document}$ hat tau = ({rm W'W}) $end{document} 1 W′x and consider the choice of the design matrix W. The case in favor of using orthogonal polynomials to comprise the elements of W and provide a PC program, written in GAUSS, for obtaining them is presented. This program can be used instead of existing tables of orthogonal polynomials in the case of equally spaced time points, and to avoid laborious hand-computation to obtain them when the time points are not equally spaced. The program also computes the corresponding orthogonal polynomial regression coefficients documentclass{article}pagestyle{empty}begin{document}$ hat alpha = (Phi 'Phi)^{ - 1} Phi '{rm x} $end{document} , where Φ consists of orthogonal polynomials, which may then be input into other programs for subsequent analysis, e.g., to compare the growth profiles of several groups of individuals. Examples of the use of the program are given. Information on obtaining a copy of the program is provided in Appendix A. © 1992 Wiley-Liss, Inc. | en_US |
dc.format.extent | 1118642 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Wiley Subscription Services, Inc., A Wiley Company | en_US |
dc.subject.other | Life and Medical Sciences | en_US |
dc.subject.other | Anthropology | en_US |
dc.title | PC program for obtaining orthogonal polynomial regression coefficients for use in longitudinal data analysis | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Medicine (General) | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Biostatistics, The University of Michigan, Ann Arbor, Michigan 48109 | en_US |
dc.contributor.affiliationum | Department of Oral Biology, The University of Michigan, Ann Arbor, Michigan 48109 | en_US |
dc.contributor.affiliationother | Department of Oral and Maxillofacial Surgery, Baylor College of Dentistry, Dallas, Texas 75246 ; Baylor College of Dentistry, 3302 Gaston Ave., Dallas, TX 75246 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/38552/1/1310040317_ftp.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1002/ajhb.1310040317 | en_US |
dc.identifier.source | American Journal of Human Biology | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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