f1.ld.f2 {nparLD}R Documentation

Nonparametric Tests for the F1-LD-F2 Design

Description

This function performs several tests for the relative treatment effects with global or patterned alternatives for the F1-LD-F2 design (see Details for the definition). For the experiments with F1-LD-F2 design, the Wald-type statistic (WTS) and the ANOVA-type statistic (ATS) are calculated.

Usage

f1.ld.f2(var, time1, time2, group, subject, time1.name="TimeC", 
time2.name="TimeT", group.name="GroupA", description=TRUE)

Arguments

var a vector of variable of interest; missing values should be specified as NA.
time1 a vector of the first sub-plot factor variable. See Details for more explanation.
time2 a vector of the second sub-plot factor variable. See Details for more explanation.
group a vector of the whole-plot factor variable. See Details for more explanation.
subject a vector of individual subjects.
time1.name name of the time1 vector; the default option is "TimeC".
time2.name name of the time2 vector; the default option is "TimeT".
group.name name of the group vector; the default option is "GroupA".
description indicator for whether a short description of the output should be shown; the default option is TRUE.

Details

The F1-LD-F2 design refers to the experimental design with one whole-plot factor and two sub-plot factors (where time2 is the stratification of time1). A whole-plot factor refers to a factor effective for each subject at all times. A sub-plot factor refers to a factor effective at a single time point for all time curves and all subjects. See Brunner et al. (2002) for more examples.

Value

A list with the following numeric components.

RTE Summary of the relative treatment effect (RTE) in a n-by-3 matrix form, where n is the total number of time1, time2, and group levels, and group-time interactions. The summary includes the mean of the ranks (RankMeans) in the 1st column, number of observations without counting the repeated measurements within the cell (Nobs) in the 2nd column, and the relative treatment effect (RTE) in the 3rd column.
Wald.test the test statistic, degrees of freedom (df), and corresponding p-value of the Wald-type test.
ANOVA.test the test statistic, degrees of freedom (df), and corresponding p-value of the ANOVA-type test.
covariance the covariance matrix.

Note

Although the function is designed to work for any kind of input (either in charactor or numeric vector) for the factor parameter(s), we recommend inputting them as numeric vector(s) after assigning each group of factors a number (i.e., 1 = first group, 2 = second group, etc.).

Author(s)

Kimihiro Noguchi, Karthinathan Thangavelu, Frank Konietschke, Yulia Gel, Edgar Brunner

References

Brunner, E., Domhof, S., and Langer, F. (2002). Nonparametric Analysis of Longitudinal Data in Factorial Experiments, Wiley, New York.

Brunner, E. and Langer, F. (1999). Nichtparametrische Analyse longitudinaler Daten, R. Oldenbourg Verlag, Munchen Wien.

See Also

ld.f1, ld.f2, f1.ld.f1, f2.ld.f1, ld.ci, edema

Examples

## Example with the "Postoperative edema" data ##
data(edema)
var<-c(edema[,"n01"],edema[,"n1"],edema[,"n3"],edema[,"n5"],
edema[,"o01"],edema[,"o1"],edema[,"o3"],edema[,"o5"])
time1<-factor(c(rep("Healthy",232),rep("Operated",232)))
time2<-c(rep(-1,58),rep(1,58),rep(3,58),rep(5,58),
rep(-1,58),rep(1,58),rep(3,58),rep(5,58))
group<-rep(edema[,"Group"],8)
subject<-rep(edema[,"Patient"],8)
ex.f1f2<-f1.ld.f2(var, time1, time2, group, subject, time1.name = "Hand", 
time2.name = "Day", group.name = "Treatment", description=FALSE)

## Wald-type statistic 
ex.f1f2$Wald.test

#$Wald.test
#                    Statistic df      p-value
#Treatment           1.0725762  1 3.003643e-01
#Hand               25.8758257  1 3.641005e-07
#Day                36.8857947  3 4.864630e-08
#Treatment:Hand      0.3304448  1 5.653973e-01
#Day:Hand           47.3460508  3 2.933702e-10
#Treatment:Day       5.3048189  3 1.507900e-01
#Treatment:Hand:Day  1.6581652  3 6.462743e-01

## ANOVA-type statistic
ex.f1f2$ANOVA.test

#                    Statistic       df      p-value
#Treatment           1.0725762 1.000000 3.003668e-01
#Hand               25.8758257 1.000000 3.647569e-07
#Day                11.0630080 2.699667 9.682198e-07
#Treatment:Hand      0.3304448 1.000000 5.653986e-01
#Day:Hand           15.1854889 2.630202 6.208596e-09
#Treatment:Day       1.3342605 2.699667 2.625598e-01
#Treatment:Hand:Day  0.7170325 2.630202 5.242392e-01

[Package nparLD version 1.1 Index]