ttests: Many 2 sample tests tests

In Rfast: A Collection of Efficient and Extremely Fast R Functions

Many 2 sample tests tests

Description

It performs very many 2 sample tests.

Usage

ttests(x, y = NULL, ina, paired = FALSE, logged = FALSE, parallel = FALSE)
mcnemars(x, y = NULL, ina, logged = FALSE) 
var2tests(x, y = NULL, ina, alternative = "unequal", logged = FALSE) 

Arguments

x	A matrix with the data, where the rows denote the samples and the columns are the variables.
y	A second matrix with the data of the second group. If this is NULL (default value) then the argument ina must be supplied. Notice that when you supply the two matrices the procedure is two times faster.
ina	A numerical vector with 1s and 2s indicating the two groups. Be careful, the function is designed to accept only these two numbers. In addition, if your "y" is NULL, you must specify "ina".
alternative	The type of hypothesis to be checked, "equal", "greater", "less".
paired	If the groups are not independent paired t-tests should be performed and this must be TRUE, otherwise, leave it FALSE. In this case, the two groups must have equal smaple sizes, otherwise no test will be performed.
logged	Should the p-values be returned (FALSE) or their logarithm (TRUE)?
parallel	Should parallel implentations take place in C++? The default value is FALSE.

Details

For the ttests, if the groups are independent, the Welch's t-test (without assuming equal variances) is performed. Otherwise many paired t-tests are performed. The McNemar's test requires a number of observations, at least 30 would be good in order for the test to have some power and be size corect.

Value

A matrix with the test statistic, the degrees of freedom (if the groups are independent) and the p-value (or their logarithm) of each test.

Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <[e-mail]> and Manos Papadakis <[e-mail]>.

References

B. L. Welch (1951). On the comparison of several mean values: an alternative approach. Biometrika, 38(3/4), 330-336.

McNemar Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika. 12(2):153-157.

See Also

ftests, anovas, ttest

Examples

## 1000 variables, hence 1000 t-tests will be performed
x = matrnorm(100, 100)
## 100 observations in total
ina = rbinom(100, 1, 0.6) + 1   ## independent samples t-test
ttests(x, ina = ina)
x1 = x[ina == 1, ]
x2 = x[ina == 2, ]
ttests(x1, x2)
x <- NULL

Rfast documentation built on Nov. 9, 2023, 5:06 p.m.