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One-at-a-Time Plans
One-at-a-time experiments are always done when the experimental system is set up to produce single results or pairs of results. When random error is small compared to main effects expected, such experiments are economical, but may give biased estimates. These biases can usually be described by two-f...
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Published in: | Journal of the American Statistical Association 1973-06, Vol.68 (342), p.353-360 |
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cites | cdi_FETCH-LOGICAL-c255t-fead3fa65981f71a8976aef3fd5f6452891b388c3b517c5405a0a3be85acdd293 |
container_end_page | 360 |
container_issue | 342 |
container_start_page | 353 |
container_title | Journal of the American Statistical Association |
container_volume | 68 |
creator | Daniel, Cuthbert |
description | One-at-a-time experiments are always done when the experimental system is set up to produce single results or pairs of results. When random error is small compared to main effects expected, such experiments are economical, but may give biased estimates. These biases can usually be described by two-factor interactions (2fi). Minimal augmentations of standard one-at-a-time sequences are given, first to separate main effects from 2fi, then to estimate each 2fi separately. Each new datum produces one or more new estimates. |
doi_str_mv | 10.1080/01621459.1973.10482433 |
format | article |
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When random error is small compared to main effects expected, such experiments are economical, but may give biased estimates. These biases can usually be described by two-factor interactions (2fi). Minimal augmentations of standard one-at-a-time sequences are given, first to separate main effects from 2fi, then to estimate each 2fi separately. Each new datum produces one or more new estimates.</description><subject>Cubes</subject><subject>Design analysis</subject><subject>Estimation bias</subject><subject>Estimators</subject><subject>Expected values</subject><subject>Experiment design</subject><subject>Experimentation</subject><subject>Factorial design</subject><subject>Factorials</subject><subject>Statistical variance</subject><subject>Theory and Methods</subject><issn>0162-1459</issn><issn>1537-274X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1973</creationdate><recordtype>article</recordtype><recordid>eNqFj01LAzEQhoMouFZP3sWD19Qkk2ySYyl-QaEeKngLs9kEtuyHJAvSf-8uteDNubwwPO8MDyF3nC05M-yR8VJwqeySWw3TShohAc5IwRVoKrT8PCfFDNGZuiRXOe_ZNNqYgtxu-0BxpEh3TRfu31vs8zW5iNjmcPObC_Lx_LRbv9LN9uVtvdpQL5QaaQxYQ8RSWcOj5misLjFEiLWKpVTCWF6BMR4qxbVXkilkCFUwCn1dCwsLUh7v-jTknEJ0X6npMB0cZ25Wcyc1N6u5k9pUfDgW93kc0t-WAKadEEYyXU7Y6og1fRxSh99Dams34qEdUkzY-yY7-OfVD10uXuM</recordid><startdate>19730601</startdate><enddate>19730601</enddate><creator>Daniel, Cuthbert</creator><general>Taylor & Francis Group</general><general>American Statistical Association</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19730601</creationdate><title>One-at-a-Time Plans</title><author>Daniel, Cuthbert</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c255t-fead3fa65981f71a8976aef3fd5f6452891b388c3b517c5405a0a3be85acdd293</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1973</creationdate><topic>Cubes</topic><topic>Design analysis</topic><topic>Estimation bias</topic><topic>Estimators</topic><topic>Expected values</topic><topic>Experiment design</topic><topic>Experimentation</topic><topic>Factorial design</topic><topic>Factorials</topic><topic>Statistical variance</topic><topic>Theory and Methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Daniel, Cuthbert</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of the American Statistical Association</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Daniel, Cuthbert</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>One-at-a-Time Plans</atitle><jtitle>Journal of the American Statistical Association</jtitle><date>1973-06-01</date><risdate>1973</risdate><volume>68</volume><issue>342</issue><spage>353</spage><epage>360</epage><pages>353-360</pages><issn>0162-1459</issn><eissn>1537-274X</eissn><abstract>One-at-a-time experiments are always done when the experimental system is set up to produce single results or pairs of results. When random error is small compared to main effects expected, such experiments are economical, but may give biased estimates. These biases can usually be described by two-factor interactions (2fi). Minimal augmentations of standard one-at-a-time sequences are given, first to separate main effects from 2fi, then to estimate each 2fi separately. Each new datum produces one or more new estimates.</abstract><pub>Taylor & Francis Group</pub><doi>10.1080/01621459.1973.10482433</doi><tpages>8</tpages></addata></record> |
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ispartof | Journal of the American Statistical Association, 1973-06, Vol.68 (342), p.353-360 |
issn | 0162-1459 1537-274X |
language | eng |
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source | JSTOR Archival Journals and Primary Sources Collection |
subjects | Cubes Design analysis Estimation bias Estimators Expected values Experiment design Experimentation Factorial design Factorials Statistical variance Theory and Methods |
title | One-at-a-Time Plans |
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