(Have searched for this already)
Hi,
How do you find the strength of correlation between two variables using an
ANOVA table? "Pr(>F)" gives the statistical significance of the
association, but not the strength of the correlation.
See data (from R) below
Readable:
"Df" "Sum Sq" "Mean
Sq" "F value"
"Pr(>F)"
"pre" 1 0.00593 0.00593936
0.7450563 0.401636958677004
"coh" 1 0.04311 0.04311302
5.4082639
0.0344751749542619
"Residuals" 15 0.11957 0.00797169 NA
NA
Original:
"Df" "Sum Sq" "Mean Sq" "F value"
"Pr(>F)"
"pre" 1 0.0059393604629317 0.0059393604629317 0.745056336657567
0.401636958677004
"coh" 1 0.0431130207164516 0.0431130207164516 5.40826398359156
0.0344751749542619
"Residuals" 15 0.119575396598395 0.00797169310655964 NA NA
Any help would be greatly appreciated,
Douglas Holmes
--
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Hi Douglas I would go for a different command then aov. something like: ?cor or ?cor.test To also get the p value of the correlation. Cheers, Tal On Sat, Apr 25, 2009 at 8:27 AM, drmh <douglasrmholmes@googlemail.com>wrote:> > (Have searched for this already) > > Hi, > > How do you find the strength of correlation between two variables using an > ANOVA table? "Pr(>F)" gives the statistical significance of the > association, but not the strength of the correlation. > > See data (from R) below > > Readable: > "Df" "Sum Sq" "Mean Sq" "F value" > "Pr(>F)" > "pre" 1 0.00593 0.00593936 > 0.7450563 0.401636958677004 > "coh" 1 0.04311 0.04311302 > 5.4082639 > 0.0344751749542619 > "Residuals" 15 0.11957 0.00797169 NA > NA > > Original: > "Df" "Sum Sq" "Mean Sq" "F value" "Pr(>F)" > "pre" 1 0.0059393604629317 0.0059393604629317 0.745056336657567 > 0.401636958677004 > "coh" 1 0.0431130207164516 0.0431130207164516 5.40826398359156 > 0.0344751749542619 > "Residuals" 15 0.119575396598395 0.00797169310655964 NA NA > > Any help would be greatly appreciated, > Douglas Holmes > -- > View this message in context: > http://www.nabble.com/ANOVA-statistics-question-tp23231563p23231563.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >-- ---------------------------------------------- My contact information: Tal Galili Phone number: 972-50-3373767 FaceBook: Tal Galili My Blogs: http://www.r-statistics.com/ http://www.talgalili.com http://www.biostatistics.co.il [[alternative HTML version deleted]]
Hi, thanks for your prompt reply In my situation, the dependent variable is "post-test" and the independent variables are "pre" and "coh". Howw would I find the correlation between coh and post with the effect of "pre" regressed using your commands? Tal Galili wrote:> > Hi Douglas > I would go for a different command then aov. > something like: > ?cor > or > ?cor.test > To also get the p value of the correlation. > > Cheers, > Tal > > > > On Sat, Apr 25, 2009 at 8:27 AM, drmh > <douglasrmholmes at googlemail.com>wrote: > >> >> (Have searched for this already) >> >> Hi, >> >> How do you find the strength of correlation between two variables using >> an >> ANOVA table? "Pr(>F)" gives the statistical significance of the >> association, but not the strength of the correlation. >> >> See data (from R) below >> >> Readable: >> "Df" "Sum Sq" "Mean Sq" "F >> value" >> "Pr(>F)" >> "pre" 1 0.00593 0.00593936 >> 0.7450563 0.401636958677004 >> "coh" 1 0.04311 0.04311302 >> 5.4082639 >> 0.0344751749542619 >> "Residuals" 15 0.11957 0.00797169 NA >> NA >> >> Original: >> "Df" "Sum Sq" "Mean Sq" "F value" "Pr(>F)" >> "pre" 1 0.0059393604629317 0.0059393604629317 0.745056336657567 >> 0.401636958677004 >> "coh" 1 0.0431130207164516 0.0431130207164516 5.40826398359156 >> 0.0344751749542619 >> "Residuals" 15 0.119575396598395 0.00797169310655964 NA NA >> >> Any help would be greatly appreciated, >> Douglas Holmes >> -- >> View this message in context: >> http://www.nabble.com/ANOVA-statistics-question-tp23231563p23231563.html >> Sent from the R help mailing list archive at Nabble.com. >> >> ______________________________________________ >> R-help at r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > > > -- > ---------------------------------------------- > > > My contact information: > Tal Galili > Phone number: 972-50-3373767 > FaceBook: Tal Galili > My Blogs: > http://www.r-statistics.com/ > http://www.talgalili.com > http://www.biostatistics.co.il > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > >-- View this message in context: http://www.nabble.com/ANOVA-statistics-question-tp23231563p23234421.html Sent from the R help mailing list archive at Nabble.com.
drmh <douglasrmholmes at googlemail.com> wrote> >Hello again, >In my situation, I have three variables: pretest, posttest, and cohesion. > >I want to work out the correlation between postest and cohesion. >cor(cohesion, posttest) gives you this.>I looked at multiple sets of data and created ANOVA tables of them. However, >as pretest and postest are sometimes correlated (with a statistical >significance < 0.05), it is necessary to discount the effect of pretest to >work out the real correlation of posttest and coherence.. I need a system >for working out the strength of the correlation between posttest and >coherence, when does actually occur.Whether pretest and posttest are correlated, and whether that correlation is statistically significant, is irrelevant to your question as posed. Correlation is defined between two variables, not among three. You might want some sort of regression such as lm(cohesion~pretest+posttest) but you might not> >According to my understanding level refers the amount or magnitude of >experimental units.What is level? You mention pretest, posttest and cohesion - now you mention level. What are these experimental units? Pretest, posttest are scores - range from any value from>0 to 1. Cohesion can be any value. > >What exactly would >cor(y[pre == 1], x[pre == 1]) >cor(y[pre == 2], x[pre == 2]) >give me? >well, you said above that pretest and posttest can range from 0 to 1; if this is the case, pre would rarely be 1 and never be 2, so the first line above wouldn't give you much, and the second wouldn't give you anything. Also, you are now using y and x instead of (presumably) cohesion and posttest, and pre instead of, presumably, pretest. Peter Peter L. Flom, PhD Statistical Consultant www DOT peterflomconsulting DOT com