Re: [R] repeated measures ANOVA - among group differences
Hm, it seems I possibly used the technical term "nested" inappropriately in my response. I meant: "If Month is a repeated measure within each Quadrat..." and "If Treatment is also a repeated measure within each Quadrat..." On Wed, Apr 1, 2009 at 8:21 AM, Mike Lawrence wrote: > If Month is nested within Quadrat I think you want: > aov(ProportioninTreatment ~ Treatment*Month +Error(Quadrat/Month), RM) > > If Treatment is also nested within Quadrat, you want: > aov(ProportioninTreatment ~ Treatment*Month > +Error(Quadrat/(Treatment*Month)), RM) > > > On Wed, Apr 1, 2009 at 12:42 AM, Jessica L Hite/hitejl/O/VCU > wrote: >> >> >> I have data on the proportion of clutches experiencing different fates >> (e.g., 4 different sources of mortality) for 5 months . I need to test 1) >> if the overall proportion of these different fates is different over the >> entire study and 2) to see if there are monthly differences within (and >> among) fate types. Thus, I am pretty sure this is an RM analysis -( I >> measure the same quadrats each month). >> >> I am fine running the analysis in R - with the code below, however, there >> is no output for the among group variation...this is an important component >> - any ideas on how to solve this problem? >> >> I have included code and sample data below. >> >> Many thanks in advance for help and suggestions. >> >> J >> >> both.aov <- aov(ProportioninTreatment ~ factor(Treatment)*factor(Month) + >> Error(factor(Quadrat)), RM) >> >> Error: factor(id) >> Df Sum Sq Mean Sq F value Pr(>F) >> Residuals 3 0.51619 0.17206 #why only partial output >> here? ### >> >> Error: Within >> Df Sum Sq Mean Sq F value Pr(>F) >> factor(Fate1) 3 1.2453 0.4151 3.5899 0.017907 * >> time 1 0.9324 0.9324 8.0637 0.005929 ** >> factor(Fate1):time 3 0.9978 0.3326 2.8763 0.042272 * >> Residuals 69 7.9783 0.1156 >> >> >> >> >> Fate1 Proportion in Fate ASIN Month Quadrat >> 1 0.117647059 0.350105778 1 1 >> 1 0 0 2 1 >> 1 0.1 0.339836909 3 1 >> 1 0 0 4 1 >> 1 0 0 5 1 >> 1 0 0 1 2 >> 1 0 0 2 2 >> 1 0.2 0.463647609 3 2 >> 1 0.25 0.523598776 4 2 >> 1 0.1 0.339836909 5 2 >> 1 0 0 1 3 >> 1 0 0 2 3 >> 1 0 0 3 3 >> 1 0.384615385 0.668964075 4 3 >> 1 0 0 5 3 >> 1 0 0 1 4 >> 1 0 0 2 4 >> 1 0 0 3 4 >> 1 0.16667 0.420534336 4 4 >> 1 0 0 5 4 >> 2 0.352941176 0.636132062 1 1 >> 2 0.2 0.463647609 2 1 >> 2 0.3 0.615479708 3 1 >> 2 1 1.570796327 4 1 >> 2 0 0 5 1 >> 2 0.5 0.785398163 1 2 >> 2 0 0 2 2 >> 2 0.6 0.886077124 3 2 >> 2 0.41667 0.701674124 4 2 >> 2 0.2 0.490882678 5 2 >> 2 0 0 1 3 >> 2 0.2 0.463647609 2 3 >> 2 0 0 3 3 >> 2 0.461538462 0.746898594 4 3 >> 2 0 0 5 3 >> 2 0 0 1 4 >> 2 0 0 2 4 >> 2 0.307692308 0.588002604 3 4 >> 2 0.7 0.955316618 4 4 >> 2 0 0 5 4 >> 3 0 0 1 1 >> 3 0 0 2 1 >> 3 0.4 0.729727656 3 1 >> 3 0 0 4 1 >> 3 1 1.570796327 5 1 >> 3 0.5 0.785398163 1 2 >> 3 0 0 2 2 >> 3 0 0 3 2 >> 3 0.25 0.523598776 4 2 >> 3 0.6 0.841068671 5 2 >> 3 0 0 1 3 >> 3 0 0 2 3 >> 3 0 0 3 3 >> 3 0.153846154 0.403057075 4 3 >> 3 0.7 0.955316618 5 3 >> 3 0 0 1 4 >> 3 0 0 2 4 >> 3 0 0 3 4 >> 3 0 0 4 4 >> 3 0.875 1.209429203 5 4 >> 4 0.294117647 0.573203309 1 1 >> 4 0.2 0.463647609 2 1 >> 4 0 0 3 1 >> 4 0 0 4 1 >> 4 0 0 5 1 >> 4 0 0 1 2 >> 4 0 0 2 2 >> 4 0 0 3 2 >> 4 0.08333 0.292842771 4 2 >> 4 0.1 0.339836909 5 2 >> 4 0 0 1 3 >> 4 0 0 2 3 >> 4 0 0 3 3 >> 4 0 0 4 3 >> 4 0.16667 0.420534336 5 3 >> 4 0 0 1 4 >> 4 0 0 2 4 >> 4 0.461538462 0.746898594 3 4 >> 4 0 0 4 4 >> 4 0.125 0.361367124 5 4 >> [[alternative HTML version deleted]] >> >> __ >> 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. >> > > > > --
Re: [R] repeated measures ANOVA - among group differences
If Month is nested within Quadrat I think you want: aov(ProportioninTreatment ~ Treatment*Month +Error(Quadrat/Month), RM) If Treatment is also nested within Quadrat, you want: aov(ProportioninTreatment ~ Treatment*Month +Error(Quadrat/(Treatment*Month)), RM) On Wed, Apr 1, 2009 at 12:42 AM, Jessica L Hite/hitejl/O/VCU wrote: > > > I have data on the proportion of clutches experiencing different fates > (e.g., 4 different sources of mortality) for 5 months . I need to test 1) > if the overall proportion of these different fates is different over the > entire study and 2) to see if there are monthly differences within (and > among) fate types. Thus, I am pretty sure this is an RM analysis -( I > measure the same quadrats each month). > > I am fine running the analysis in R - with the code below, however, there > is no output for the among group variation...this is an important component > - any ideas on how to solve this problem? > > I have included code and sample data below. > > Many thanks in advance for help and suggestions. > > J > > both.aov <- aov(ProportioninTreatment ~ factor(Treatment)*factor(Month) + > Error(factor(Quadrat)), RM) > > Error: factor(id) > Df Sum Sq Mean Sq F value Pr(>F) > Residuals 3 0.51619 0.17206 #why only partial output > here? ### > > Error: Within > Df Sum Sq Mean Sq F value Pr(>F) > factor(Fate1) 3 1.2453 0.4151 3.5899 0.017907 * > time 1 0.9324 0.9324 8.0637 0.005929 ** > factor(Fate1):time 3 0.9978 0.3326 2.8763 0.042272 * > Residuals 69 7.9783 0.1156 > > > > > Fate1 Proportion in Fate ASIN Month Quadrat > 1 0.117647059 0.350105778 1 1 > 1 0 0 2 1 > 1 0.1 0.339836909 3 1 > 1 0 0 4 1 > 1 0 0 5 1 > 1 0 0 1 2 > 1 0 0 2 2 > 1 0.2 0.463647609 3 2 > 1 0.25 0.523598776 4 2 > 1 0.1 0.339836909 5 2 > 1 0 0 1 3 > 1 0 0 2 3 > 1 0 0 3 3 > 1 0.384615385 0.668964075 4 3 > 1 0 0 5 3 > 1 0 0 1 4 > 1 0 0 2 4 > 1 0 0 3 4 > 1 0.16667 0.420534336 4 4 > 1 0 0 5 4 > 2 0.352941176 0.636132062 1 1 > 2 0.2 0.463647609 2 1 > 2 0.3 0.615479708 3 1 > 2 1 1.570796327 4 1 > 2 0 0 5 1 > 2 0.5 0.785398163 1 2 > 2 0 0 2 2 > 2 0.6 0.886077124 3 2 > 2 0.41667 0.701674124 4 2 > 2 0.2 0.490882678 5 2 > 2 0 0 1 3 > 2 0.2 0.463647609 2 3 > 2 0 0 3 3 > 2 0.461538462 0.746898594 4 3 > 2 0 0 5 3 > 2 0 0 1 4 > 2 0 0 2 4 > 2 0.307692308 0.588002604 3 4 > 2 0.7 0.955316618 4 4 > 2 0 0 5 4 > 3 0 0 1 1 > 3 0 0 2 1 > 3 0.4 0.729727656 3 1 > 3 0 0 4 1 > 3 1 1.570796327 5 1 > 3 0.5 0.785398163 1 2 > 3 0 0 2 2 > 3 0 0 3 2 > 3 0.25 0.523598776 4 2 > 3 0.6 0.841068671 5 2 > 3 0 0 1 3 > 3 0 0 2 3 > 3 0 0 3 3 > 3 0.153846154 0.403057075 4 3 > 3 0.7 0.955316618 5 3 > 3 0 0 1 4 > 3 0 0 2 4 > 3 0 0 3 4 > 3 0 0 4 4 > 3 0.875 1.209429203 5 4 > 4 0.294117647 0.573203309 1 1 > 4 0.2 0.463647609 2 1 > 4 0 0 3 1 > 4 0 0 4 1 > 4 0 0 5 1 > 4 0 0 1 2 > 4 0 0 2 2 > 4 0 0 3 2 > 4 0.08333 0.292842771 4 2 > 4 0.1 0.339836909 5 2 > 4 0 0 1 3 > 4 0 0 2 3 > 4 0 0 3 3 > 4 0 0 4 3 > 4 0.16667 0.420534336 5 3 > 4 0 0 1 4 > 4 0 0 2 4 > 4 0.461538462 0.746898594 3 4 > 4 0 0 4 4 > 4 0.125 0.361367124 5 4 > [[alternative HTML version deleted]] > > __ > 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. > -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tinyurl.com/mikes-public-calendar ~ Certainty is folly... I think. ~ __ 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 provid
[R] repeated measures ANOVA - among group differences
I have data on the proportion of clutches experiencing different fates (e.g., 4 different sources of mortality) for 5 months . I need to test 1) if the overall proportion of these different fates is different over the entire study and 2) to see if there are monthly differences within (and among) fate types. Thus, I am pretty sure this is an RM analysis -( I measure the same quadrats each month). I am fine running the analysis in R - with the code below, however, there is no output for the among group variation...this is an important component - any ideas on how to solve this problem? I have included code and sample data below. Many thanks in advance for help and suggestions. J both.aov <- aov(ProportioninTreatment ~ factor(Treatment)*factor(Month) + Error(factor(Quadrat)), RM) Error: factor(id) Df Sum Sq Mean Sq F value Pr(>F) Residuals 3 0.51619 0.17206 #why only partial output here? ### Error: Within Df Sum Sq Mean Sq F value Pr(>F) factor(Fate1) 3 1.2453 0.4151 3.5899 0.017907 * time1 0.9324 0.9324 8.0637 0.005929 ** factor(Fate1):time 3 0.9978 0.3326 2.8763 0.042272 * Residuals 69 7.9783 0.1156 Fate1 Proportion in Fate ASIN Month Quadrat 1 0.117647059 0.350105778 1 1 1 0 0 2 1 1 0.1 0.339836909 3 1 1 0 0 4 1 1 0 0 5 1 1 0 0 1 2 1 0 0 2 2 1 0.2 0.463647609 3 2 1 0.25 0.523598776 4 2 1 0.1 0.339836909 5 2 1 0 0 1 3 1 0 0 2 3 1 0 0 3 3 1 0.384615385 0.668964075 4 3 1 0 0 5 3 1 0 0 1 4 1 0 0 2 4 1 0 0 3 4 1 0.16667 0.420534336 4 4 1 0 0 5 4 2 0.352941176 0.636132062 1 1 2 0.2 0.463647609 2 1 2 0.3 0.615479708 3 1 2 1 1.570796327 4 1 2 0 0 5 1 2 0.5 0.785398163 1 2 2 0 0 2 2 2 0.6 0.886077124 3 2 2 0.41667 0.701674124 4 2 2 0.2 0.490882678 5 2 2 0 0 1 3 2 0.2 0.463647609 2 3 2 0 0 3 3 2 0.461538462 0.746898594 4 3 2 0 0 5 3 2 0 0 1 4 2 0 0 2 4 2 0.307692308 0.588002604 3 4 2 0.7 0.955316618 4 4 2 0 0 5 4 3 0 0 1 1 3 0 0 2 1 3 0.4 0.729727656 3 1 3 0 0 4 1 3 1 1.570796327 5 1 3 0.5 0.785398163 1 2 3 0 0 2 2 3 0 0 3 2 3 0.25 0.523598776 4 2 3 0.6 0.841068671 5 2 3 0 0 1 3 3 0 0 2 3 3 0 0 3 3 3 0.153846154 0.403057075 4 3 3 0.7 0.955316618 5 3 3 0 0 1 4 3 0 0 2 4 3 0 0 3 4 3 0 0 4 4 3 0.875 1.209429203 5 4 4 0.294117647 0.573203309 1 1 4 0.2 0.463647609 2 1 4 0 0 3 1 4 0 0 4 1 4 0 0 5 1 4 0 0 1 2 4 0 0 2 2 4 0 0 3 2 4 0.08333 0.292842771 4 2 4 0.1 0.339836909 5 2 4 0 0 1 3 4 0 0 2 3 4 0 0 3 3 4 0 0 4 3 4 0.16667 0.420534336 5 3 4 0 0 1 4 4 0 0 2 4 4 0.461538462 0.746898594 3 4 4 0 0 4 4 4 0.125 0.361367124 5 4 [[alternative HTML version deleted]] __ 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.
