A Global Test for the Goodness of Fit of Generalized Linear Models : An Estimating Equation Approach
Summary Generalized linear models are used to analyze a wide variety of discrete and continuous data with possible overdispersion under the assumption that the data follow an exponential family of distributions. The violation of this assumption may have adverse effects on the statistical inferences....
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Veröffentlicht in: | Bulletin - Calcutta Statistical Association 2005-03, Vol.56 (1-4), p.251-282 |
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creator | Rao, R. Prabhakar Sutradhar, B.C. |
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Generalized linear models are used to analyze a wide variety of discrete and continuous data with possible overdispersion under the assumption that the data follow an exponential family of distributions. The violation of this assumption may have adverse effects on the statistical inferences. The existing goodness of fit tests for checking this assumption are valid only for a standard exponential family of distributions with no overdispersion. In this paper, we develop a global goodness of fit test for the general exponential family of distributions which may or may not contain overdispersion. The proposed statistic has asymptotically standard Gaussian distribution which should be easy to implement. |
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Generalized linear models are used to analyze a wide variety of discrete and continuous data with possible overdispersion under the assumption that the data follow an exponential family of distributions. The violation of this assumption may have adverse effects on the statistical inferences. The existing goodness of fit tests for checking this assumption are valid only for a standard exponential family of distributions with no overdispersion. In this paper, we develop a global goodness of fit test for the general exponential family of distributions which may or may not contain overdispersion. The proposed statistic has asymptotically standard Gaussian distribution which should be easy to implement.</description><identifier>ISSN: 0008-0683</identifier><identifier>EISSN: 2456-6462</identifier><identifier>DOI: 10.1177/0008068320050514</identifier><language>eng</language><publisher>New Delhi, India: SAGE Publications</publisher><ispartof>Bulletin - Calcutta Statistical Association, 2005-03, Vol.56 (1-4), p.251-282</ispartof><rights>2005 SAGE Publications</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0008068320050514$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0008068320050514$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,780,784,21819,27924,27925,43621,43622</link.rule.ids></links><search><creatorcontrib>Rao, R. Prabhakar</creatorcontrib><creatorcontrib>Sutradhar, B.C.</creatorcontrib><title>A Global Test for the Goodness of Fit of Generalized Linear Models : An Estimating Equation Approach</title><title>Bulletin - Calcutta Statistical Association</title><description>Summary
Generalized linear models are used to analyze a wide variety of discrete and continuous data with possible overdispersion under the assumption that the data follow an exponential family of distributions. The violation of this assumption may have adverse effects on the statistical inferences. The existing goodness of fit tests for checking this assumption are valid only for a standard exponential family of distributions with no overdispersion. In this paper, we develop a global goodness of fit test for the general exponential family of distributions which may or may not contain overdispersion. The proposed statistic has asymptotically standard Gaussian distribution which should be easy to implement.</description><issn>0008-0683</issn><issn>2456-6462</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNp1ULFOwzAUtBBIVKU74_uBwLMTOzZbVLUBqYile-TYThsU7GKnA3w9icqExHQn3bvTvSPknuIDpWX5iIgShcwZIkdOiyuyYAUXmSgEuyaLWc5m_ZasUupbzFExKQVfEFtBPYRWD7B3aYQuRBiPDuoQrHcpQehg248z1M67qIf-21nY9d7pCK_BuiHBE1QeNmnsP_TY-wNsPs8TCR6q0ykGbY535KbTQ3KrX1yS_XazXz9nu7f6ZV3tMkMLNWZlKWSpaOswd5KhsYIrayU3FpllojXTG6WwhqqCcoVcCRStLTqmWSsNz5cEL7EmhpSi65pTnDrFr4ZiM-_U_N1psmQXS9IH17yHc_RTwf_vfwCAT2Xj</recordid><startdate>200503</startdate><enddate>200503</enddate><creator>Rao, R. Prabhakar</creator><creator>Sutradhar, B.C.</creator><general>SAGE Publications</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>200503</creationdate><title>A Global Test for the Goodness of Fit of Generalized Linear Models : An Estimating Equation Approach</title><author>Rao, R. Prabhakar ; Sutradhar, B.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c149t-7768791be03e820cd659dd85cd02d26bc00876dc194159059606bd4f2a2b8c53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rao, R. Prabhakar</creatorcontrib><creatorcontrib>Sutradhar, B.C.</creatorcontrib><collection>CrossRef</collection><jtitle>Bulletin - Calcutta Statistical Association</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rao, R. Prabhakar</au><au>Sutradhar, B.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Global Test for the Goodness of Fit of Generalized Linear Models : An Estimating Equation Approach</atitle><jtitle>Bulletin - Calcutta Statistical Association</jtitle><date>2005-03</date><risdate>2005</risdate><volume>56</volume><issue>1-4</issue><spage>251</spage><epage>282</epage><pages>251-282</pages><issn>0008-0683</issn><eissn>2456-6462</eissn><abstract>Summary
Generalized linear models are used to analyze a wide variety of discrete and continuous data with possible overdispersion under the assumption that the data follow an exponential family of distributions. The violation of this assumption may have adverse effects on the statistical inferences. The existing goodness of fit tests for checking this assumption are valid only for a standard exponential family of distributions with no overdispersion. In this paper, we develop a global goodness of fit test for the general exponential family of distributions which may or may not contain overdispersion. The proposed statistic has asymptotically standard Gaussian distribution which should be easy to implement.</abstract><cop>New Delhi, India</cop><pub>SAGE Publications</pub><doi>10.1177/0008068320050514</doi><tpages>32</tpages></addata></record> |
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title | A Global Test for the Goodness of Fit of Generalized Linear Models : An Estimating Equation Approach |
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