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| {{notability|date=July 2011}}
| | What is RSS? <br><br> |
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| In [[statistics]], the '''standardized mean of a contrast variable (SMCV''' or '''SMC)''', is a parameter assessing [[effect size]]. The SMCV is defined as [[mean]] divided by the [[standard deviation]] of a [[Contrast (statistics)|contrast variable]].<ref name=ZhangBook2011>{{cite book | | RSS suggests Really Simple Syndication. RSS is a specific format based o-n XML, that was first used to unite headers with site content. In reality, RSS feeds are XML files containing information according to the RSS specification, and usually found on an internet site. <br><br>As soon as a rss appears in-the Internet, any connected computer can get access to it. In order for the consumer to have the ability to use the FEED, he needs specific software or services called readers or aggregators. <br><br>RSS allows users to save yourself their time, however it is pretty difficult to produce an RSS feed physically. That is why currently there are certainly a lot of programs that do not require XML or RSS knowledge to utilize them. These programs enable you to create RSS feeds in WYSIWYG mode, as well as keep and update it. I found out about [http://www.iamsport.org/pg/bookmarks/cdcard9/read/26882677/quick-begin-to-creating-your-first-blog http://auromere.com/] by browsing webpages. One of such programs is Feed Editor (http://www.extralabs.net/) that"s some additional functionality besides editing RSS feeds. <br><br>The RSS technology will be earnestly developed and used in different areas. It is likely that in the foreseeable future it will maybe not be possible to produce a successful website with no RSS-FEED. <br><br>Why Use RSS? <br><br>RSS will help you save time - you"ll be able to get latest data using only one special system or web service, if you are a person. In the event people need to get more on [http://www.iamsport.org/pg/bookmarks/auromerecomcritiquenpq/read/26932373/mining-in-scandinavia go], we know of many databases people should investigate. RSS will bring information to you from sites, boards, sites from everywhere in the Net. Besides, RSS records are very small, therefore it will even save your traffic. For another standpoint, consider looking at: [http://www.streetfire.net/profile/auromerecomcritiquetit.htm this page is not affiliated]. <br><br>RSS will help you increase the acceptance of one"s site along with its quality, if you are a site owner. Sometimes internet site becomes common only because giving an interesting FEED. Using RSS today is known as a good sort especially that it"s super easy to add an RSS feed to your site. Do not forget to update your feed often and it"ll fructify. <br><br>How-to Read RSS? <br><br>You need a specific system (or service) for reading feeds, to benefit from RSS. Today, there are always a lot of such applications, both free and commercial. You dont need any particular application, because Opera can acquire and read RSS feeds, if you use Opera (or IE 7.0, Maxthon). Needless to say, Opera is a visitor first of all, therefore it doesnt have all functions of a sophisticated RSS reader. We have already compiled the set of full featured RSS readers: <br><br>http://www.yeahreader.com - Extremely popular free RSS audience and information aggregator (Windows ); <br><br>http://www.bloglines.com - On line RSS reader; <br><br>How-to Produce RSS? <br><br>To produce RSS, you can use special online services or desktop applications. Moreover, if you are not afraid of difficulties, you could write the code of your supply physically, since RSS is dependant on XML. <br><br>Windows applications: <br><br>http://www.webvigour.com/ <br><br>http://www.extralabs.net/ <br><br>How to Promote RSS? <br><br>Various practices are employed to advertise RSS feeds. Probably the most trusted one is submitting of the supply file in to specific search-engines and directories. You can use the following services: <br><br>http://feedshark.brainbliss.com/ <br><br>http://www.submitrssfeed.com/ <br><br>Besides submitting, every other practices usually used to promote the web site may also be used to promote the feed..<br><br>When you adored this informative article in addition to you would want to obtain more info with regards to health insurance plan ([http://www.blogigo.com/woebegonegather23 click this over here now]) i implore you to pay a visit to our own webpage. |
| |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
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| |url= |isbn=978-0-521-73444-8}}</ref><ref name=ZhangPharmacogenomics2009>{{cite journal |author=Zhang XHD
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| |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
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| |year=2009 |month= |pmid=20397965 |doi=10.2217/14622416.10.3.345 |url=}}</ref>
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| The SMCV was first proposed for one-way [[ANOVA]] cases
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| <ref name="ZhangPharmacogenomics2009"/>
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| and was then extended to multi-factor [[ANOVA]] cases
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| .<ref name=ZhangPharmacogenomics2010>{{cite journal |author=Zhang XHD
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| |title= Assessing the size of gene or RNAi effects in multifactor high-throughput experiments
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| |journal=Pharmacogenomics |volume=11 |issue= |pages=199–213
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| |year=2010 |month= |pmid= 20136359|doi=10.2217/PGS.09.136 |url=}}</ref>
| |
| | |
| ==Background==
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| Consistent interpretations for the strength of group comparison, as represented by a contrast, are important.<ref name=RosenthaletalBook2000>{{cite book
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| |author= Rosenthal R, Rosnow RL, Rubin DB
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| |year=2000
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| |title= Contrasts and Effect Sizes in Behavioral Research
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| |publisher =Cambridge University Press
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| |url= |isbn=0-521-65980-9}}</ref><ref name=Huberty2002>{{cite journal |author=Huberty CJ
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| |title= A history of effect size indices
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| |journal=Educational and Psychological Measurement |volume=62 |issue= |pages=227–40
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| |year=2002 |month= |pmid= |doi=10.1177/0013164402062002002 |url=}}</ref>
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| The standardized mean of a contrast variable, along with [[c+-probability|c<sup>+</sup>-probability]]
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| , can provide a consistent interpretation of the strength of a comparison.<ref name=ZhangJBiometBiostat2010>{{cite journal |author=Zhang XHD
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| |title= Contrast variable potentially providing a consistent interpretation to effect sizes
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| |journal=Journal of Biometrics & Biostatistics |volume=1 |issue= |pages=108
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| |year=2010 |month= |pmid= |doi=10.4172/2155-6180.1000108
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| |url= http://www.omicsonline.org/2155-6180/2155-6180-1-108.php}}</ref> When there are only two groups involved in a comparison, SMCV is the same as [[SSMD]]. SSMD belongs to a popular type of effect-size measure called "standardized mean differences"<ref name=Kirk1996>{{cite journal |author=Kirk RE
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| |title= Practical significance: A concept whose time has come
| |
| |journal=Educational and Psychological Measurement |volume=56 |issue= |pages=746–59
| |
| |year=1996 |month= |pmid= |doi= 10.1177/0013164496056005002 |url=}}</ref> which includes Cohen's <math>d</math><ref name=Cohen1962>{{cite journal |author=Cohen J
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| |title= The statistical power of abnormal-social psychological research: A review
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| |journal= Journal of Abnormal and Social Psychology |volume=65 |issue= |pages=145–53
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| |year=1962 |month= |pmid= 13880271 |doi= |url=}}</ref> and Glass's <math> \delta.</math><ref name=Glass1976>{{cite journal |author=Glass GV
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| |title= Primary, secondary, and meta-analysis of research
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| |journal= Educational Researcher |volume=5 |issue= |pages=3–8
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| |year=1976 |month= |pmid= |doi= 10.3102/0013189X005010003 |url=}}</ref>
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| In [[ANOVA]], a similar parameter for measuring the strength of group comparison is standardized effect size (SES).<ref>{{cite journal |author=Steiger JH
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| |title= Beyond the F test: Effect size confidence intervals and tests of close fit in the analysis of variance and contrast analysis
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| |journal= Psychological Methods |volume=9 |issue= |pages=164–82
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| |year=2004 |month= |pmid= |doi= |url=}}</ref> One issue with SES is that its values are incomparable for contrasts with different coefficients. SMCV does not have such an issue.
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| | |
| ==Concept==
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| Suppose the random values in t groups represented by random variables <math>G_1, G_2, \ldots, G_t </math> have means <math>\mu_1, \mu_2, \ldots, \mu_t </math> and variances <math>\sigma_1^2, \sigma_2^2, \ldots, \sigma_t^2 </math>, respectively. A contrast variable <math>V</math> is defined by
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| :<math>V=\sum_{i=1}^t c_i G_i ,</math>
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| where the <math>c_i</math>'s are a set of coefficients representing a comparison of interest and satisfy <math>\sum_{i=1}^t c_i = 0</math>. The SMCV of contrast variable <math>V</math>, denoted by <math>\lambda</math>, is defined as<ref name="ZhangBook2011"/>
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| | |
| :<math>\lambda = \frac{\operatorname{E}(V)}{\operatorname{stdev}(V)}
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| =\frac{\sum_{i=1}^t c_i \mu_i}{\sqrt{\text{Var}(\sum_{i=1}^t c_i G_i)}}
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| =\frac{\sum_{i=1}^t c_i \mu_i}{\sqrt{\sum_{i=1}^t c_i^2 \sigma_i^2 + 2\sum_{i=1}^t \sum_{j=i} c_i c_j \sigma_{ij} }} </math>
| |
| | |
| where <math> \sigma_{ij}</math> is the covariance of <math>G_{i}</math> and <math>G_{j}</math>. When <math>G_1, G_2, \ldots, G_t </math> are independent,
| |
| | |
| :<math>\lambda = \frac{\sum_{i=1}^t c_i \mu_i}{\sqrt{\sum_{i=1}^t c_i^2 \sigma_i^2 }}. </math>
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| | |
| ==Classifying rule for the strength of group comparisons==
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| The population value (denoted by <math>\lambda</math> ) of SMCV can be used to classify the strength of a comparison represented by a [[contrast variable]], as shown in the following table.<ref name="ZhangBook2011"/><ref name="ZhangPharmacogenomics2009"/>
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| This classifying rule has a probabilistic basis due to the link between SMCV and [[c+-probability|c<sup>+</sup>-probability]].<ref name="ZhangBook2011"/>
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| | |
| {| class="wikitable"
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| |-
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| ! Effect type !! Effect subtype !!Thresholds for negative SMCV !! Thresholds for positive SMCV
| |
| |-
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| |rowspan=4|Extra large ||Extremely strong || <math>\lambda \le -5</math> || <math>\lambda \ge 5</math>
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| |-
| |
| |Very strong || <math>-5 < \lambda \le -3</math> || <math> 5 > \lambda \ge 3</math>
| |
| |-
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| |Strong || <math>-3 < \lambda \le -2</math> || <math> 3 > \lambda \ge 2</math>
| |
| |-
| |
| |Fairly strong || <math>-2 < \lambda \le -1.645</math> || <math> 2 > \lambda \ge 1.645</math>
| |
| |-
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| | rowspan=2|Large ||Moderate || <math>-1.645 < \lambda \le -1.28</math> || <math>1.645 > \lambda \ge 1.28</math>
| |
| |-
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| |Fairly moderate || <math>-1.28 < \lambda \le -1</math> || <math>1.28 > \lambda \ge 1</math>
| |
| |-
| |
| | rowspan=3|Medium ||Fairly weak || <math>-1 < \lambda \le -0.75</math> || <math> 1 > \lambda \ge 0.75</math>
| |
| |-
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| |Weak || <math>-0.75 < \lambda < -0.5</math> || <math> 0.75 > \lambda > 0.5</math>
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| |-
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| |Very weak || <math>-0.5 \le \lambda < -0.25</math> || <math>0.5 \ge \lambda > 0.25</math>
| |
| |-
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| | rowspan=2|Small ||Extremely weak || <math>-0.25 \le \lambda < 0</math> || <math>0.25 \ge \lambda > 0</math>
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| |-
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| |No effect || colspan=2 | <math> \lambda = 0</math>
| |
| |}
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| ==Statistical estimation and inference==
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| The estimation and inference of SMCV presented below is for one-factor experiments.<ref name="ZhangBook2011"/><ref name="ZhangPharmacogenomics2009"/>
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| Estimation and inference of SMCV for multi-factor experiments has also been discussed.<ref name="ZhangBook2011"/><ref name="ZhangPharmacogenomics2010"/><ref name="ZhangJBiometBiostat2010"/>
| |
| | |
| The estimation of SMCV relies on how samples are obtained in a study. When the groups are correlated, it is usually difficult to estimate the covariance among groups. In such a case, a good strategy is to obtain matched or paired samples (or subjects) and to conduct contrast analysis based on the matched samples. A simple example of matched contrast analysis is the analysis of paired difference of drug effects after and before taking a drug in the same patients. By contrast, another strategy is to not match or pair the samples and to conduct contrast analysis based on the unmatched or unpaired samples. A simple example of unmatched contrast analysis is the comparison of efficacy between a new drug taken by some patients and a standard drug taken by other patients. Methods of estimation for SMCV and c<sup>+</sup>-probability in matched contrast analysis may differ from those used in unmatched contrast analysis.
| |
| | |
| ===Unmatched samples===
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| Consider an independent sample of size <math>n_i</math>,
| |
| | |
| : <math>Y_i=(Y_{i1}, Y_{i2}, \ldots, Y_{i n_i})</math>
| |
| | |
| from the <math>i^\text{th} (i=1, 2, \ldots, t)</math> group <math>G_i</math>.
| |
| <math>Y_i</math>'s are independent. Let <math>\bar{Y}_i = \frac{1}{n_i} \sum_{j=1}^{n_i} Y_{ij}</math>,
| |
| | |
| : <math>s_i^2 = \frac{1}{n_i-1} \sum_{j=1}^{n_i} (Y_{ij}-\bar{Y}_i)^2,</math>
| |
| : <math>N = \sum_{i=1}^t n_i</math>
| |
| and
| |
| : <math>\text{MSE } =\frac{1}{N-t} \sum_{i=1}^t (n_i-1)s_i^2.</math>
| |
| | |
| When the <math>t</math> groups have unequal variance, the maximal likelihood estimate (MLE) and method-of-moment estimate (MM) of SMCV (<math>\lambda</math>) are, respectively<ref name="ZhangBook2011"/><ref name="ZhangPharmacogenomics2009"/>
| |
| :<math>\hat{\lambda}_\text{MLE } | |
| = \frac{\sum_{i=1}^t c_i \bar{Y}_i}{\sqrt{\sum_{i=1}^t \frac{n_i-1}{n_i}c_i^2 s_i^2 }} </math>
| |
| and
| |
| :<math>\hat{\lambda}_\text{MM} | |
| = \frac{\sum_{i=1}^t c_i \bar{Y}_i}{\sqrt{\sum_{i=1}^t c_i^2 s_i^2 }}. </math>
| |
| | |
| When the <math>t</math> groups have equal variance, under normality assumption, the uniformly minimal variance unbiased estimate (UMVUE) of SMCV (<math>\lambda</math>) is<ref name="ZhangBook2011"/><ref name="ZhangPharmacogenomics2009"/>
| |
| :<math>\hat{\lambda}_\text{UMVUE}
| |
| = \sqrt\frac{K}{N-t}
| |
| \frac{\sum_{i=1}^t c_i \bar{Y}_i}{\sqrt{\sum_{i=1}^t \text{MSE } c_i^2 }} </math>
| |
| where <math>K = \frac{2 (\Gamma(\frac{N-t}{2}) )^2}{(\Gamma(\frac{N-t-1}{2}) )^2}</math>. The confidence interval of SMCV can be made using the following [[non-central t-distribution]]:<ref name="ZhangBook2011"/><ref name="ZhangPharmacogenomics2009"/>
| |
| :<math>T = \frac{\sum_{i=1}^t c_i \bar{Y}_i}{\sqrt{\sum_{i=1}^t \text{MSE } c_i^2/n_i }} \sim \text{noncentral } t(N-t, b\lambda) </math> | |
| where <math>b=\sqrt{\frac{\sum_{i=1}^t c_i^2}{\sum_{i=1}^t c_i^2/n_i}}. </math>
| |
| | |
| ===Matched samples===
| |
| In matched contrast analysis, assume that there are <math>n</math> independent samples <math>(Y_{1j}, Y_{2j}, \cdots, Y_{tj})</math> from <math>t</math> groups (<math>G_i</math>'s), where <math>i = 1, 2, \cdots, t; j = 1, 2, \cdots, n</math>. Then
| |
| the <math>j^\text{th}</math> observed value of a contrast
| |
| <math>V = \sum_{i=1}^t c_i G_i</math> is <math>v_j = \sum_{i=1}^t c_i Y_i</math>.
| |
| Let <math>\bar{V}</math> and <math>s_V^2</math> be the sample mean and sample variance of the contrast variable <math>V</math>, respectively. Under normality assumptions, the [[Minimum-variance unbiased estimator|UMVUE]] estimate of SMCV is<ref name="ZhangBook2011"/>
| |
| :<math>\hat{\lambda}_\text{UMVUE}
| |
| = \sqrt\frac{K}{n-1}\frac{\bar{V}}{s_V } </math>
| |
| where <math>K = \frac{2 (\Gamma(\frac{n-1}{2}) )^2}{(\Gamma(\frac{n-2}{2}) )^2}.</math>
| |
| | |
| A [[confidence interval]] for SMCV can be made using the following [[non-central t-distribution]]:<ref name="ZhangBook2011"/>
| |
| :<math>T = \frac{\bar{V}}{s_V/\sqrt{n} } \sim \text{noncentral } t(n-1, \sqrt{n}\lambda). </math>
| |
| | |
| ==See also==
| |
| * [[Dual-flashlight plot]]
| |
| | |
| ==References==
| |
| {{reflist}}
| |
| | |
| {{DEFAULTSORT:SMCV}}
| |
| [[Category:Effect size]]
| |
| [[Category:Analysis of variance]]
| |
What is RSS?
RSS suggests Really Simple Syndication. RSS is a specific format based o-n XML, that was first used to unite headers with site content. In reality, RSS feeds are XML files containing information according to the RSS specification, and usually found on an internet site.
As soon as a rss appears in-the Internet, any connected computer can get access to it. In order for the consumer to have the ability to use the FEED, he needs specific software or services called readers or aggregators.
RSS allows users to save yourself their time, however it is pretty difficult to produce an RSS feed physically. That is why currently there are certainly a lot of programs that do not require XML or RSS knowledge to utilize them. These programs enable you to create RSS feeds in WYSIWYG mode, as well as keep and update it. I found out about http://auromere.com/ by browsing webpages. One of such programs is Feed Editor (http://www.extralabs.net/) that"s some additional functionality besides editing RSS feeds.
The RSS technology will be earnestly developed and used in different areas. It is likely that in the foreseeable future it will maybe not be possible to produce a successful website with no RSS-FEED.
Why Use RSS?
RSS will help you save time - you"ll be able to get latest data using only one special system or web service, if you are a person. In the event people need to get more on go, we know of many databases people should investigate. RSS will bring information to you from sites, boards, sites from everywhere in the Net. Besides, RSS records are very small, therefore it will even save your traffic. For another standpoint, consider looking at: this page is not affiliated.
RSS will help you increase the acceptance of one"s site along with its quality, if you are a site owner. Sometimes internet site becomes common only because giving an interesting FEED. Using RSS today is known as a good sort especially that it"s super easy to add an RSS feed to your site. Do not forget to update your feed often and it"ll fructify.
How-to Read RSS?
You need a specific system (or service) for reading feeds, to benefit from RSS. Today, there are always a lot of such applications, both free and commercial. You dont need any particular application, because Opera can acquire and read RSS feeds, if you use Opera (or IE 7.0, Maxthon). Needless to say, Opera is a visitor first of all, therefore it doesnt have all functions of a sophisticated RSS reader. We have already compiled the set of full featured RSS readers:
http://www.yeahreader.com - Extremely popular free RSS audience and information aggregator (Windows );
http://www.bloglines.com - On line RSS reader;
How-to Produce RSS?
To produce RSS, you can use special online services or desktop applications. Moreover, if you are not afraid of difficulties, you could write the code of your supply physically, since RSS is dependant on XML.
Windows applications:
http://www.webvigour.com/
http://www.extralabs.net/
How to Promote RSS?
Various practices are employed to advertise RSS feeds. Probably the most trusted one is submitting of the supply file in to specific search-engines and directories. You can use the following services:
http://feedshark.brainbliss.com/
http://www.submitrssfeed.com/
Besides submitting, every other practices usually used to promote the web site may also be used to promote the feed..
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