MCT | R Documentation |
The MCT function calculates the multiplication combination tests for testig H0m or H0p hypothesis for matched pairs with missingness in both arms. For testing the Behrens-Fisher problem H0p: p = 1/2, MCT is based upon permutation versions of the Munzel (1999) (paired) and Brunner and Munzel (2002) (unpaired) tests. And, For testing the null hypothesis H0m: mu1 = mu2, MCT is based upon the randomization version of the paired t-test (Konietschke and Pauly, 2014) and Janssen's permutation version for the Welch test (Janssen, 1997) for paired and unpaired data respectively.
MCT(
x,
y,
hypothesis = c("h0m", "h0p"),
alternative = c("two.sided", "less", "greater"),
nperm = 10000,
alpha = 0.05
)
x |
a (non-empty) numeric vector of data values representing the first components of the pairs. |
y |
a (non-empty) numeric vector of data values representing the second components of the pairs. |
hypothesis |
a character string indicating which hypothesis is to be tested, must be either 'h0m' (default) or 'h0p'. |
alternative |
a character string specifying the alternative hypothesis, must be one of 'two.sided' (default), 'greater' or 'less'. You can specify just the initial letter. |
nperm |
The number of permutations used for calculating the permutation tests. The default option is 10,000. |
alpha |
A number specifying the significance level; the default is 0.05. |
A MCT
object containing the following components:
Input |
The data input of the user. |
Descriptive |
Some descriptive statistics of the data. Displayed are the number of individuals per variable, the mean, and variance. |
MCT |
The value of the test staistics of the completely observed and the incompletely observed data and the p-value of the permutation procedure of each test, as well as the overall test decision of the multiplication combination test. |
Janssen, A. (1997). Studentized permutation tests for non-iid hypotheses and the generalized Behrens-Fisher problem. Statistics & probability letters, 36(1), 9-21.
Munzel, U.(1999). Nonparametric methods for paired samples. Statistica Neerlandica, 53(3), 277-286.
Brunner, E., Munzel, U. (2000). The Nonparametric Behrens-Fisher Problem: Asymptotic Theory and a Small Sample Approximation. Biometrical Journal 42, 17 -25.
Konietschke, F., & Pauly, M. (2014). Bootstrapping and permuting paired t-test type statistics. Statistics and Computing, 24(3), 283-296.
Amro, L., Konietschke, F., and Pauly, M.(2019). Multiplication-combination tests for incomplete paired data. Statistics in Medicince, 38(17), 3243-3255.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.