Analysis of binary data in the presence of non-Bernoulli sources of variation

Graduate Thesis Or Dissertation

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Citeable URL: https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/p5547t72h

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Attribute Name	Values
Creator	Sands, Bradley Roy
Abstract	A quantal response model, more general than the usual logistic model, is introduced. This model takes into account sources of variability, or experimental error, other than that arising from variability in response between individual organisms (or other objects on test). It is assumed that this extra source of variation is additive on a logistic scale. The likelihood function for this model is displayed and procedures relating to a likelihood analysis are discussed. An approximate least squares approach is also introduced. A class of tests and a class of estimators (of the scale parameter for this extra source of variation) are examined.
Resource Type	Dissertation
Date Available	2013-11-05T20:55:37+00:00
Date Issued	1975-08-14
Degree Level	Doctoral
Degree Name	Doctor of Philosophy (Ph.D.)
Degree Field	Statistics
Degree Grantor	Oregon State University
Commencement Year	1976
Advisor	Pierce, Donald A.
Academic Affiliation	Statistics
Non-Academic Affiliation	Oregon State University. Graduate School
Subject	Variables (Mathematics)
Urheberrechts-Erklärung	Copyright Not Evaluated
Publisher	Oregon State University
Peer Reviewed	No
Language	English [eng]
Digitization Specifications	File scanned at 300 ppi (Monochrome) using ScandAll PRO 1.8.1 on a Fi-6770A in PDF format. CVista PdfCompressor 5.0 was used for pdf compression and textual OCR.
Replaces	http://hdl.handle.net/1957/43786

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