2026-09-19T21:07:38Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/82016 2023-07-11 col_2142_5131 col_2142_11614 com_2142_5130 com_2142_11613 com_2142_8903

Budescu, David V. Johnson, Timothy Robin 2015-09-25T20:38:42Z 2015-09-25T20:38:42Z 10000-01-01 2001 2001 In this dissertation I propose a general statistical modeling framework for the purpose of making inferences concerning the external correspondence (i.e., calibration and discrimination) of probability judgments. The statistical model is based on a new stochastic judgment model which is expressed as a mixed-effects ordinal probit regression model. This model can be used to derive several new model-based measures of external correspondence as well as establishing a means of deriving the sampling/posterior distributions of such measures. Issues of model specification and inference for applied research are discussed in detail. Several detailed examples are given. Made available in DSpace on 2015-09-25T20:38:42Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3030442.pdf: 6945163 bytes, checksum: 4d988a45e4470f12d655e2103f034dc0 (MD5) Previous issue date: 2001 Embargo set by: Seth Robbins for item 83297 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs U of I Only 166 p. Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2001. http://hdl.handle.net/2142/82016 (MiAaPQ)AAI3030442 eng Statistics On the Use of Mixed -Effects Models for the Analysis of Probability Judgments text Psychology Psychology University of Illinois at Urbana-Champaign Dissertation Ph.D.