Comparison of Li–Wong and loglinear mixed models for the statistical analysis of oligonucleotide arrays | Zendy

TzuMing Chu | Zendy; B. S. Weir | Zendy; Russell D. Wolfinger | Zendy

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Comparison of Li–Wong and loglinear mixed models for the statistical analysis of oligonucleotide arrays

Author(s) -

TzuMing Chu,

B. S. Weir,

Russell D. Wolfinger

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btg435

Subject(s) - computer science , set (abstract data type) , statistic , data set , multiplicative function , estimator , additive model , statistics , statistical model , mixed model , variance (accounting) , statistical hypothesis testing , test statistic , data mining , algorithm , mathematics , mathematical analysis , accounting , business , programming language

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.

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