summary.rmfanova | R Documentation |
Prints the summary of the repeated measures functional analysis of variance.
## S3 method for class 'rmfanova'
summary(object, ...)
object |
a "rmfanova" object. |
... |
integer indicating the number of decimal places to be used to present the numerical results.
It can be named |
The function prints out the information about the number of samples \ell
,
number of observations n
, number of design time points p
,
adjustment method for pairwise comparison tests (if \ell>2
), test statistics,
and p-values of tests performed by the rmfanova()
function.
No return value, called for side effects.
# Some of the examples may run some time.
# preparation of the DTI data set, for details see Kurylo and Smaga (2023)
library(refund)
data(DTI)
# MS patients
DTI_ms <- DTI[DTI$case == 1, ]
miss_data <- c()
for (i in 1:340) if (any(is.na(DTI_ms$cca[i, ]))) miss_data <- c(miss_data, i)
DTI_ms <- DTI_ms[-miss_data, ]
DTI_ms_2 <- DTI_ms[DTI_ms$Nscans == 4, ]
xx <- vector("list", 4)
for (i in 1:4) {
xx[[i]] <- DTI_ms_2$cca[DTI_ms_2$visit == i, ]
}
xx[[1]] <- xx[[1]][-14, ]
xx[[3]] <- xx[[3]][-14, ]
yy <- xx
for (i in seq_len(4)) yy[[i]] <- yy[[i]][1:17, ]
# testing without parallel computing and multiple generation of Gaussian processes
res <- rmfanova(yy)
summary(res, digits = 3)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.