Estimation of Error Rates in Discriminant Analysis with Selection of Variables
Accurate estimation of misclassification rates in discriminant analysis with selection of variables by, for example, a stepwise algorithm, is complicated by the large optimistic bias inherent in standard estimators such as those obtained by the resubstitution method. Application of a bootstrap adjus...
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| Veröffentlicht in: | Biometrics 1989-03, Vol.45 (1), p.289-299 |
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| container_end_page | 299 |
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| container_title | Biometrics |
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| creator | Snapinn, Steven M. Knoke, James D. |
| description | Accurate estimation of misclassification rates in discriminant analysis with selection of variables by, for example, a stepwise algorithm, is complicated by the large optimistic bias inherent in standard estimators such as those obtained by the resubstitution method. Application of a bootstrap adjustment can reduce the bias of the resubstitution method; however, the bootstrap technique requires the variable selection procedure to be repeated many times and is therefore difficult to compute. In this paper we propose a smoothed estimator that requires relatively little computation and which, on the basis of a Monte Carlo sampling study, is found to perform generally at least as well as the bootstrap method. |
| doi_str_mv | 10.2307/2532053 |
| format | Article |
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Application of a bootstrap adjustment can reduce the bias of the resubstitution method; however, the bootstrap technique requires the variable selection procedure to be repeated many times and is therefore difficult to compute. In this paper we propose a smoothed estimator that requires relatively little computation and which, on the basis of a Monte Carlo sampling study, is found to perform generally at least as well as the bootstrap method.</description><identifier>ISSN: 0006-341X</identifier><identifier>EISSN: 1541-0420</identifier><identifier>DOI: 10.2307/2532053</identifier><identifier>PMID: 2720056</identifier><identifier>CODEN: BIOMA5</identifier><language>eng</language><publisher>Malden, MA: Biometric Society</publisher><subject>Algorithms ; Analytical estimating ; Biological and medical sciences ; Biometrics ; Biometry ; Bootstrap resampling ; Discriminant analysis ; Discriminants ; Error rates ; Estimation bias ; Estimation methods ; Estimators ; Fundamental and applied biological sciences. Psychology ; General aspects ; Heart Failure - metabolism ; Heart Failure - mortality ; Hormones ; Humans ; Mathematics in biology. Statistical analysis. Models. Metrology. 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Application of a bootstrap adjustment can reduce the bias of the resubstitution method; however, the bootstrap technique requires the variable selection procedure to be repeated many times and is therefore difficult to compute. In this paper we propose a smoothed estimator that requires relatively little computation and which, on the basis of a Monte Carlo sampling study, is found to perform generally at least as well as the bootstrap method.</description><subject>Algorithms</subject><subject>Analytical estimating</subject><subject>Biological and medical sciences</subject><subject>Biometrics</subject><subject>Biometry</subject><subject>Bootstrap resampling</subject><subject>Discriminant analysis</subject><subject>Discriminants</subject><subject>Error rates</subject><subject>Estimation bias</subject><subject>Estimation methods</subject><subject>Estimators</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects</subject><subject>Heart Failure - metabolism</subject><subject>Heart Failure - mortality</subject><subject>Hormones</subject><subject>Humans</subject><subject>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</subject><subject>Models, Biological</subject><subject>Models, Statistical</subject><subject>Monte Carlo Method</subject><subject>Regression Analysis</subject><subject>Sampling Studies</subject><issn>0006-341X</issn><issn>1541-0420</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1989</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kElPwzAQhS0EKqUgfgGSDyynwNiOneRYlbJIFUhs4hY5zli4ygJ2KtR_T1ADnDiNRvPNm3mPkEMG51xAcsGl4CDFFhkzGbMIYg7bZAwAKhIxe90leyEs-zaTwEdkxBMOINWY3M1D52rdubahraVz71tPH3SHgbqGXrpgvKtdo5uOThtdrYML9NN1b_QRKzQ_ay_aO11UGPbJjtVVwIOhTsjz1fxpdhMt7q9vZ9NFZISQXWQLFLEqdVwyLpDbDEWhAC0YTE2qVFyUkJUWNHIW24xpbRQrsxgKRMmTQkzI6Ub33bcfKwxdXvevYlXpBttVyJM0y5RiqgfPNqDxbQgebf7eG9J-nTPIv5PLh-R68miQXBU1lr_cEFU_PxnmOhhdWa8b48KfXKYSmfZ2JuR4wy1D1_p_z30B0kyAeQ</recordid><startdate>19890301</startdate><enddate>19890301</enddate><creator>Snapinn, Steven M.</creator><creator>Knoke, James D.</creator><general>Biometric Society</general><general>Blackwell</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>19890301</creationdate><title>Estimation of Error Rates in Discriminant Analysis with Selection of Variables</title><author>Snapinn, Steven M. ; Knoke, James D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c335t-fbe346da4d123e2f9e3b60ef0ce8c8664bd09df0ae214f91aac61d940bee527b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1989</creationdate><topic>Algorithms</topic><topic>Analytical estimating</topic><topic>Biological and medical sciences</topic><topic>Biometrics</topic><topic>Biometry</topic><topic>Bootstrap resampling</topic><topic>Discriminant analysis</topic><topic>Discriminants</topic><topic>Error rates</topic><topic>Estimation bias</topic><topic>Estimation methods</topic><topic>Estimators</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects</topic><topic>Heart Failure - metabolism</topic><topic>Heart Failure - mortality</topic><topic>Hormones</topic><topic>Humans</topic><topic>Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)</topic><topic>Models, Biological</topic><topic>Models, Statistical</topic><topic>Monte Carlo Method</topic><topic>Regression Analysis</topic><topic>Sampling Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Snapinn, Steven M.</creatorcontrib><creatorcontrib>Knoke, James D.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Biometrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Snapinn, Steven M.</au><au>Knoke, James D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of Error Rates in Discriminant Analysis with Selection of Variables</atitle><jtitle>Biometrics</jtitle><addtitle>Biometrics</addtitle><date>1989-03-01</date><risdate>1989</risdate><volume>45</volume><issue>1</issue><spage>289</spage><epage>299</epage><pages>289-299</pages><issn>0006-341X</issn><eissn>1541-0420</eissn><coden>BIOMA5</coden><abstract>Accurate estimation of misclassification rates in discriminant analysis with selection of variables by, for example, a stepwise algorithm, is complicated by the large optimistic bias inherent in standard estimators such as those obtained by the resubstitution method. Application of a bootstrap adjustment can reduce the bias of the resubstitution method; however, the bootstrap technique requires the variable selection procedure to be repeated many times and is therefore difficult to compute. In this paper we propose a smoothed estimator that requires relatively little computation and which, on the basis of a Monte Carlo sampling study, is found to perform generally at least as well as the bootstrap method.</abstract><cop>Malden, MA</cop><pub>Biometric Society</pub><pmid>2720056</pmid><doi>10.2307/2532053</doi><tpages>11</tpages></addata></record> |
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| ispartof | Biometrics, 1989-03, Vol.45 (1), p.289-299 |
| issn | 0006-341X 1541-0420 |
| language | eng |
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| source | Jstor Complete Legacy; MEDLINE; JSTOR Mathematics & Statistics |
| subjects | Algorithms Analytical estimating Biological and medical sciences Biometrics Biometry Bootstrap resampling Discriminant analysis Discriminants Error rates Estimation bias Estimation methods Estimators Fundamental and applied biological sciences. Psychology General aspects Heart Failure - metabolism Heart Failure - mortality Hormones Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Models, Biological Models, Statistical Monte Carlo Method Regression Analysis Sampling Studies |
| title | Estimation of Error Rates in Discriminant Analysis with Selection of Variables |
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