You seem to be bringing in a ton of stuff without looking at features in base R...
Check help(mauchly.test) help(anova.mlm) and examples therein. There are also options in the "car" package. -pd > On 23 Nov 2018, at 11:43 , Lisa van der Burgh <[email protected]> wrote: > > Hi Everyone, > > > > I have a question about Mixed-Design Anova in R. I want to obtain Mauchly�s > test of Sphericity and the Greenhouse-Geisser correction. I have managed to > do it in SPSS: > > > > GLM Measure1 Measure2 Measure3 Measure4 Measure5 Measure6 BY Grouping > > /WSFACTOR=Measure 6 Polynomial > > /METHOD=SSTYPE(3) > > /PLOT=PROFILE(Measure*Grouping) > > /CRITERIA=ALPHA(.05) > > /WSDESIGN=Measure > > /DESIGN=Grouping. > > > > I have tried to replicate this in R: > > library("dplyr") > > library("tidyr") > > library("ggplot2") > > library("ez") > > > > PatientID <- c(1:10) > > Measure1 <- c(3,5,7,4,NA,7,4,4,7,2) > > Measure2 <- c(1,2,5,6,8,9,5,NA,6,7) > > Measure3 <- c(3,3,5,7,NA,4,5,7,8,1) > > Measure4 <- c(1,2,5,NA,3,NA,6,7,3,6) > > Measure5 <- c(2,3,NA,8,3,5,6,3,6,4) > > Measure6 <- c(1,2,4,6,8,3,5,6,NA,4) > > Grouping <- c(1,0,1,1,1,0,0,1,1,0) > > dataframe <- data.frame(PatientID, Measure1, Measure2, Measure3, Measure4, > Measure5, Measure6, Grouping) > > dataframe$Grouping <- as.factor(dataframe$Grouping) > > dataframe > > > > ezPrecis(dataframe) > > glimpse(dataframe) > > > > dataframe %>% count(PatientID) > > > > dataframe %>% count(PatientID, Grouping, Measure1, Measure2, Measure3, > Measure4, Measure5, Measure6) %>% > > filter(PatientID %in% c(1:243)) %>% > > print(n = 10) > > > > # So, we have a mixed design with one between factor (Grouping) and 6 within > factors (Measure 1 to 6). > > > > dat_means <- dataframe %>% > > group_by(Grouping, Measure1, Measure2, Measure3, Measure4, Measure5, > Measure6) %>% > > summarise(mRT = mean(c(Measure1, Measure2, Measure3, Measure4, Measure5, > Measure6))) %>% ungroup() > > View(dat_means) > > > > ggplot(dat_means, aes(c(Measure1, Measure2, Measure3, Measure4, Measure5, > Measure6), mRT, colour = Grouping)) + > > geom_line(aes(group = Grouping)) + > > geom_point(aes(shape = Grouping), size = 3) + > > facet_wrap(~group) > > > > ANOVA <- ezANOVA(dat, x, PatientID, within = .( c(Measure1, Measure2, > Measure3, Measure4, Measure5, Measure6)), > > between = Grouping, type = 3) > > > > print(ANOVA) > > > > > > However, this does not work. I know I am probably doing it completely wrong, > but I do not know how to solve it. Besides that, I do not know what to fill > in at the �x�. > > Can somebody help me? > > > > Thank you in advance. > > Lisa > > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] 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. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: [email protected] Priv: [email protected] ______________________________________________ [email protected] 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.
