{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T00:27:59Z","timestamp":1766449679409},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2004,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: Li and Wong have described some useful statistical models for probe-level, oligonucleotide array data based on a multiplicative parametrization. In earlier work, we proposed similar analysis-of-variance-style mixed models fit on a log scale. With only subtle differences in the specification of their mean and stochastic error components, a question arises as to whether these models could lead to varying conclusions in practical application.<\/jats:p>\n               <jats:p>Results: In this paper, we provide an empirical comparison of the two models using a real data set, and find the models perform quite similarly across most genes, but with some interesting and important distinctions. We also present results from a simulation study designed to assess inferential properties of the models, and propose a modified test statistic for the Li\u2013Wong model that provides an improvement in Type 1 error control. Advantages of both methods include the ability to directly assess and account for key sources of variability in the chip data and a means to automate statistical quality control.<\/jats:p>\n               <jats:p>Availability: The Li\u2013Wong models are available in dChip: http:\/\/www.biostat.harvard.edu\/complab\/dchip\/, and both methods will be commercially available in the forthcoming SAS Microarray Solution.<\/jats:p>\n               <jats:p>Supplementary information: Supplementary material is available at http:\/\/statgen.ncsu.edu\/ggibson\/Pubs.htm<\/jats:p>","DOI":"10.1093\/bioinformatics\/btg435","type":"journal-article","created":{"date-parts":[[2004,2,27]],"date-time":"2004-02-27T17:23:07Z","timestamp":1077902587000},"page":"500-506","source":"Crossref","is-referenced-by-count":15,"title":["Comparison of Li\u2013Wong and loglinear mixed models for the statistical analysis of oligonucleotide arrays"],"prefix":"10.1093","volume":"20","author":[{"given":"Tzu-Ming","family":"Chu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B.S.","family":"Weir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Russell D.","family":"Wolfinger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2004,1,22]]},"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/20\/4\/500\/48905275\/bioinformatics_20_4_500.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/20\/4\/500\/48905275\/bioinformatics_20_4_500.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T18:22:01Z","timestamp":1674670921000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/20\/4\/500\/192364"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004,1,22]]},"references-count":0,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2004,3,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btg435","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2004,3,1]]},"published":{"date-parts":[[2004,1,22]]}}}