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dc.creatorKuleck, Walter J.en_US
dc.creatorKnight, Catherine C.en_US
dc.date.accessioned2006-07-07T18:24:40Z
dc.date.available2006-07-07T18:24:40Z
dc.date.issued2000-04en_US
dc.identifier.citationThe Ohio Journal of Science. v100, n2 (April, 2000), 8-12en_US
dc.identifier.issn0030-0950en_US
dc.identifier.urihttp://hdl.handle.net/1811/23846
dc.descriptionAuthor Institution: The Hennepin Group ; The Department of Educational Foundations and Leadershipen_US
dc.description.abstractMany scientific disciplines involve the study of growth, development, evolution, or other kinds of multidimensional or hierarchical change processes. The order in which these changes occur can be important to the scientist. Further, understanding these changes may depend on determining not only the order in which they occur, but also the relationships among them. As the broader perspectives now obtaining in science challenge our previous assumptions of linearity and simple sequences, we increasingly require techniques that allow us to view change in a more complex, combining and branching fashion, but with the discipline of statistical rigor.en_US
dc.format.extent572507 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleAn Ordinal Sequencing Technique for Assessing Multidimensional or Hierarchical Change Modelsen_US


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