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#REDIRECT [[Contrast (statistics)]]
A '''contrast variable''' is defined as a linear combination of random variables
(with each variable representing random values in one of multiple groups involved in a comparison) instead of group means, with the restriction of the coefficients in the combination summing to zero
<ref name=ZhangPharmacogenomics2009>{{cite journal |author=Zhang XHD
|title= A method for effectively comparing gene effects in multiple conditions in RNAi and expression-profiling research
|journal=Pharmacogenomics |volume=10 |issue= |pages=345-58
|year=2009 |month= |pmid= |doi=10.2217/PGS.09.1 |url=}}</ref>
. Associated with a contrast variable are two terms, standardized mean of
contrast variable (SMCV) and c+-probability. The SMCV is the ratio of mean to standard deviation of a contrast variable and the c+-probability is the probability that a contrast variable obtains a positive value. Traditional [[contrast]] is a statistical parameter defined only on the group [[mean]]s. A contrast variable allows us to consider not only group [[mean]]s but also group [[variance]]s in a comparison. In addition, the concept of contrast variable can help to derive the [[effect size]]s across any number of groups readily and smoothly
<ref name=ZhangJBiometBiostat2010>{{cite journal |author=Zhang XHD
|title= Contrast variable potentially providing a consistent interpretation to effect sizes
|journal=Journal of Biometrics & Biostatistics |volume=1 |issue= |pages=108
|year=2010 |month= |pmid= |doi= doi:10.4172/2155-6180.1000108
|url= http://www.omicsonline.org/2155-6180/2155-6180-1-108.php}}</ref>
.
The concepts of contrast variable, SMC and c+-probability were recently proposed for one-way [[ANOVA]] cases
<ref name=ZhangPharmacogenomics2009>{{cite journal |author=Zhang XHD
|title= A method for effectively comparing gene effects in multiple conditions in RNAi and expression-profiling research
|journal=Pharmacogenomics |volume=10 |issue= |pages=345-58
|year=2009 |month= |pmid= |doi=10.2217/PGS.09.1 |url=}}</ref>
and were then extended to multi-factor [[ANOVA]] cases
<ref name=ZhangPharmacogenomics2010>{{cite journal |author=Zhang XHD
|title= Assessing the size of gene or RNAi effects in multifactor high-throughput experiments
|journal=Pharmacogenomics |volume=11 |issue= |pages=199-213
|year=2010 |month= |pmid= |doi=10.2217/PGS.09.136 |url=}}</ref>
<ref name=ZhangJBiometBiostat2010>{{cite journal |author=Zhang XHD
|title= Contrast variable potentially providing a consistent interpretation to effect sizes
|journal=Journal of Biometrics & Biostatistics |volume=1 |issue= |pages=108
|year=2010 |month= |pmid= |doi= doi:10.4172/2155-6180.1000108
|url= http://www.omicsonline.org/2155-6180/2155-6180-1-108.php}}</ref>
. When there are two groups involved in a comparison, SMCV becomes [[SSMD]]. The contrast variable, SMCV and c+-probability are critical for deriving statistical methods for assessing [[siRNA]] effects in genome-scale RNAi screens
<ref name=ZhangBook2011>{{cite book
|author= Zhang XHD
|year=2011
|title= Optimal High-Throughput Screening: Practical Experimental Design and Data Analysis for Genome-scale RNAi Research
|publisher =Cambridge University Press
|url=
|isbn=978-0-521-73444-8}}</ref>
.
==See also==
* [[Effect size]]
* [[SSMD]]
==References==
{{reflist}}
{{DEFAULTSORT:Contrast variable}}
[[Category:Effect size]]
[[Category:Analysis of Variance]]
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