angelo.arcadi at virgilio.it
2015-Nov-23 23:58 UTC
[R] Is manova() correct for this analysis?
Dear list members, I have to perform the following analysis but I do not know which function in R must be used. My guess is to use manova(). During an experiment I presented participants with some sound stimuli and I asked them to modify two parameters of the sound (Centroid and Sound_Level_Peak) to reach a given experimental goal. The initial sounds (preset sounds) had a value for those two parameters. What I am interested in is whether participants' modifications of the two parameters of the sound stimuli resulted in values actually different from the initial values of the parameters of the preset sounds. To give an idea, some rows of my data set are the following:> head(scrd)Stimulus_Type Centroid Sound_Level_Peak Preset Stimulus_A 1960.2 -20.963 no Stimulus_A 5317.2 -42.741 no ..... Stimulus_B 11256.0 -16.480 no Stimulus_B 9560.3 -19.682 no ..... ..... Stimulus_A 1900.2 -18.63 yes Stimulus_A 5617.6 -44.41 yes Stimulus_B 12056.0 -17.80 yes Stimulus_B 8960.5 -21.82 yes This is the analysis I performed with manova():> fit <- manova(cbind(Centroid,Sound_Level_Peak)~ Stimulus_Type*Preset, data=scrd) > summary(fit, test="Pillai")Df Pillai approx F num Df den Df Pr(>F) Stimulus_Type 11 0.91888 106.629 22 2760 < 2e-16 *** Preset 1 0.00343 2.371 2 1379 0.09378 . Stimulus_Type:Preset 11 0.01155 0.729 22 2760 0.81348 Residuals 1380 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1>If I am not wrong, these results say that for each stimulus type there is no difference between the patterns of the two parameters in the preset and modified conditions. Can anyone please tell me if I am correct or suggest how to perform in R such an analysis? Thanks in advance Best Angelo [[alternative HTML version deleted]]
This list is about R programming. Yours is a statistical question. Although there is certainly a nonempty intersection (and someone may attempt a response), statistical questions are better directed to a statistical list like stats.stackexchange.com. Cheers, Bert Bert Gunter "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." -- Clifford Stoll On Mon, Nov 23, 2015 at 3:58 PM, angelo.arcadi at virgilio.it <angelo.arcadi at virgilio.it> wrote:> Dear list members, > I have to perform the following analysis but I do not know which function in R > must be used. My guess is to use manova(). > > During an experiment I presented participants with some sound stimuli and I asked them to > modify two parameters of the sound (Centroid and Sound_Level_Peak) to reach a given > experimental goal. The initial sounds (preset sounds) had a value for those two parameters. > What I am interested in is whether participants' modifications of the two parameters of the > sound stimuli resulted in values actually different from the initial values of the parameters > of the preset sounds. > > To give an idea, some rows of my data set are the following: > >> head(scrd) > Stimulus_Type Centroid Sound_Level_Peak Preset > Stimulus_A 1960.2 -20.963 no > Stimulus_A 5317.2 -42.741 no > ..... > Stimulus_B 11256.0 -16.480 no > Stimulus_B 9560.3 -19.682 no > ..... > ..... > Stimulus_A 1900.2 -18.63 yes > Stimulus_A 5617.6 -44.41 yes > Stimulus_B 12056.0 -17.80 yes > Stimulus_B 8960.5 -21.82 yes > > > This is the analysis I performed with manova(): > >> fit <- manova(cbind(Centroid,Sound_Level_Peak)~ Stimulus_Type*Preset, data=scrd) >> summary(fit, test="Pillai") > Df Pillai approx F num Df den Df Pr(>F) > Stimulus_Type 11 0.91888 106.629 22 2760 < 2e-16 *** > Preset 1 0.00343 2.371 2 1379 0.09378 . > Stimulus_Type:Preset 11 0.01155 0.729 22 2760 0.81348 > Residuals 1380 > --- > Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 >> > > If I am not wrong, these results say that for each stimulus type there is no difference > between the patterns of the two parameters in the preset and modified conditions. > > Can anyone please tell me if I am correct or suggest how to perform in R such an analysis? > > Thanks in advance > > Best > > Angelo > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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.