An Improved Goodness of Fit Statistic for Probability Prediction Models
We consider the general case of probability prediction models having two or more outcomes and propose an adjusted χ2 statistic which can be used to assess the goodness of fit of these models. We present a simulation study to show that our proposed statistic has an approximate χ2 distribution under t...
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| Veröffentlicht in: | Biometrical journal 1999-03, Vol.41 (1), p.71-82 |
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| container_title | Biometrical journal |
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| creator | Pigeon, Joseph G. Heyse, Joseph F. |
| description | We consider the general case of probability prediction models having two or more outcomes and propose an adjusted χ2 statistic which can be used to assess the goodness of fit of these models. We present a simulation study to show that our proposed statistic has an approximate χ2 distribution under the null hypothesis. Two applications are provided to illustrate the use of the new statistic. The first application examines the fit of a logistic regression model using both the proposed statistic and the popular Hosmer‐Lemeshow statistic and we compare and contrast these two methods. The second application evaluates the goodness of fit of a polychotomous regression model. |
| doi_str_mv | 10.1002/(SICI)1521-4036(199903)41:1<71::AID-BIMJ71>3.0.CO;2-O |
| format | Article |
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The second application evaluates the goodness of fit of a polychotomous regression model.</description><subject>Exact sciences and technology</subject><subject>Goodness of fit</subject><subject>Inference from stochastic processes; time series analysis</subject><subject>Linear inference, regression</subject><subject>Logistic regression</subject><subject>Mathematics</subject><subject>Polychotomous regression</subject><subject>Probability and statistics</subject><subject>Probability prediction models</subject><subject>Probability theory and stochastic processes</subject><subject>Sciences and techniques of general use</subject><subject>Statistics</subject><subject>Stochastic processes</subject><issn>0323-3847</issn><issn>1521-4036</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><recordid>eNp9kU1v1DAQhi0EEkvhP-SAUHvIMrbjOFk-pG2WboNaglRQexs5jiMZsnEbp8D-e7zKajkU9TQja_zMq2cI-UBhTgHY2-OrsihPqGA0ToCnxzTPc-AnCV3Q95IuFstyFZ-Wl58l_cjnMC-qdyyunpDZ4cdTMgPOeMyzRD4nL7z_AQA5JGxG1ss-Kje3g_tlmmjtXNMb7yPXRmd2jK5GNVo_Wh21boi-Dq5Wte3suA29aawereujS9eYzr8kz1rVefNqX4_I97NP34rz-KJal8XyItYJ5DSuTQ1UZApakRglWlCirkVIEqqQaZZlteBaMsPS0Mg65YpqMDJrjOKsZfyIvJm4IfLdvfEjbqzXputUb9y9R0YhZ5Ql_BBAD877wbR4O9iNGrZIAXdaEXdacScJd5Jw0ooJRYqSIgatOGlFjoBFhQyrwH29D6C8Vl07qF5b_w-ecS6kCGPX09hv25ntg92Pr_7v5v1LIMcTOVzG_DmQ1fATU8mlwOsvazzPxc1qdZNhwv8C5O2lxw</recordid><startdate>199903</startdate><enddate>199903</enddate><creator>Pigeon, Joseph G.</creator><creator>Heyse, Joseph F.</creator><general>WILEY-VCH Verlag Berlin GmbH</general><general>WILEY‐VCH Verlag Berlin GmbH</general><general>Wiley-VCH</general><scope>BSCLL</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>199903</creationdate><title>An Improved Goodness of Fit Statistic for Probability Prediction Models</title><author>Pigeon, Joseph G. ; Heyse, Joseph F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4091-beb0158a0f54ea5f0a5bb5042a5b576888b53c72e26b537b63a1c0e78dea32f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Exact sciences and technology</topic><topic>Goodness of fit</topic><topic>Inference from stochastic processes; time series analysis</topic><topic>Linear inference, regression</topic><topic>Logistic regression</topic><topic>Mathematics</topic><topic>Polychotomous regression</topic><topic>Probability and statistics</topic><topic>Probability prediction models</topic><topic>Probability theory and stochastic processes</topic><topic>Sciences and techniques of general use</topic><topic>Statistics</topic><topic>Stochastic processes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pigeon, Joseph G.</creatorcontrib><creatorcontrib>Heyse, Joseph F.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Biometrical journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pigeon, Joseph G.</au><au>Heyse, Joseph F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Improved Goodness of Fit Statistic for Probability Prediction Models</atitle><jtitle>Biometrical journal</jtitle><addtitle>Biom. 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| identifier | ISSN: 0323-3847 |
| ispartof | Biometrical journal, 1999-03, Vol.41 (1), p.71-82 |
| issn | 0323-3847 1521-4036 |
| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Exact sciences and technology Goodness of fit Inference from stochastic processes time series analysis Linear inference, regression Logistic regression Mathematics Polychotomous regression Probability and statistics Probability prediction models Probability theory and stochastic processes Sciences and techniques of general use Statistics Stochastic processes |
| title | An Improved Goodness of Fit Statistic for Probability Prediction Models |
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