An object of class "htest"
performing a \(z\)-test for Cuzick and Edwards \(T_{run}\) test statistic
which is based on the number of consecutive cases from the cases in the data under RL or CSR independence.
Under RL of \(n_1\) cases and \(n_0\) controls to the given locations in the study region, \(T_{run}\) approximately has \(N(E[T_{run}],Var[T_{run}])\) distribution for large \(n\).
The argument cc.lab
is case-control label, 1 for case, 0 for control, if the argument case.lab
is NULL
,
then cc.lab
should be provided in this fashion, if case.lab
is provided, the labels are converted to 0's
and 1's accordingly.
The logical argument var.sim (default=FALSE
) is for using the simulation estimated variance or the exact
variance for the variance of \(T_{run}\) in its standardization.
If var.sim=TRUE
, the simulation estimated variance is used for \(Var[T_{run}]\) (see varTrun.sim
),
otherwise the exact variance (see varTrun
) is used.
Moreover, when var.sim=TRUE
, the argument Nvar.sim
represents the number of resamplings
(without replacement) in the RL scheme, with default being 1000
.
The function varTrun
might take a very long time when data size is large (even larger than 50);
in this case, it is recommended to use var.sim=TRUE
in this function.
See also (cuzick:1990;textualnnspat) and the references therein.
ZTrun(
dat,
cc.lab,
alternative = c("two.sided", "less", "greater"),
conf.level = 0.95,
case.lab = NULL,
var.sim = FALSE,
Nvar.sim = 1000,
...
)
A list
with the elements
The \(Z\) test statistic for the Cuzick and Edwards \(T_{run}\) test
The \(p\)-value for the hypothesis test for the corresponding alternative
Confidence interval for the Cuzick and Edwards \(T_{run}\) value
at the given confidence level conf.level
and depends on the type of alternative
.
Estimate of the parameter, i.e., the Cuzick and Edwards \(T_{run}\) value.
Hypothesized null value for the Cuzick and Edwards \(T_{run}\) value which is \(n_1 (n_1-1)/(n_0+1)\) for this function.
Type of the alternative hypothesis in the test, one of "two.sided"
, "less"
, "greater"
Description of the hypothesis test
Name of the data set, dat
The data set in one or higher dimensions, each row corresponds to a data point.
Case-control labels, 1 for case, 0 for control
Type of the alternative hypothesis in the test, one of "two.sided"
, "less"
or "greater"
.
Level of the upper and lower confidence limits, default is 0.95
,
for Cuzick and Edwards \(T_{run}\) statistic
The label used for cases in the cc.lab
(if cc.lab
is not provided then the labels are converted
such that cases are 1 and controls are 0), default is NULL
.
A logical argument (default is FALSE
) to determine whether the simulation estimated variance or
the exact variance be used for the variance of \(T_{run}\) in its standardization.
If var.sim=TRUE
, the simulation estimated variance is used for \(Var[T_{run}]\) (see varTrun.sim
),
otherwise the exact variance (see varTrun
) is used.
The number of simulations, i.e., the number of resamplings under the RL scheme to estimate the
variance of \(T_{run}\), used only when var.sim=TRUE
.
are for further arguments, such as method
and p
, passed to the dist
function.
Elvan Ceyhan
ceTrun
, ZceTk
, and ZTcomb
n<-20 #or try sample(1:20,1) #try also 40, 50, 60
set.seed(123)
Y<-matrix(runif(3*n),ncol=3)
cls<-sample(0:1,n,replace = TRUE) #or try cls<-rep(0:1,c(10,10))
ZTrun(Y,cls)
ZTrun(Y,cls,method="max")
ZTrun(Y,cls,var.sim=TRUE)
ZTrun(Y,cls+1,case.lab = 2,alt="l") #try also ZTrun(Y,cls,conf=.9,alt="g")
#cls as a factor
na<-floor(n/2); nb<-n-na
fcls<-rep(c("a","b"),c(na,nb))
ZTrun(Y,fcls,case.lab="a")
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