Description Usage Arguments Details Value See Also Examples
Calculate the p-value for continous variables. The decision which test to use is equal to m.cont.
The p-value is calculated using one of the four tests: Wilcoxon-Test, t-Test, Kruskal-Test, Anova.
1  | p.cont(x, group, paired = F, is.ordered = F, nonparametric = F, t.log = F, var.equal = F, index = c(), create = "tex")
 | 
x | 
 Vector of the continous variable.  | 
group | 
 Vector of the grouping variable.  | 
paired | 
 Logical. Is the categorial Variable paired?  | 
is.ordered | 
 Logical. Is the categorial Variable ordered?  | 
nonparametric | 
 Logical. Should the continuous variable tested by using non-parametric methods.  | 
t.log | 
 Logical. Should be used the log of the original data.  | 
var.equal | 
 Logical. Should variances be assumed to be equal when applying t-tests?  | 
index | 
 Optional. Label for the footnote. The footnotes aren't produced in this function.  | 
create | 
 Which output document should be produced in the following step (one of "pdf", "tex", "knitr", or "word").  | 
Wilcoxon Test: A nonparametric Test for a comparison of 2 dependent samples. (see wilcox.test).
Mann-Whitney-U Test: A nonparametric Test for a comparison of 2 independent samples. (see wilcox.test).
t-Test: A parametric Test for a comparison of 2 (in)dependent samples. (see t.test).
Friedman-Test: A nonparametric Test for a comparison of more than 2 dependent samples. (see friedman.test).
Anova Type III: A parametric Test for a comparison of more than 2 dependent samples. (see Anova with ).
Kruskal-Wallis-Test: A nonparametric Test for a comparison of more than 2 independent samples. (see kruskal.test).
Anova: A parametric Test for a comparison of more than 2 independent samples. (see aov).
The p-value with index which test is ussed is returned. author Lorenz Uhlmann, Csilla van Lunteren
lme
Anova
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