colanovas: Many Welch's F-tests

View source: R/many_regression_models_correlations.R

Many Welch's F-testsR Documentation

Many Welch's F-tests

Description

Many Welch's F-tests.

Usage

colanovas(y, x, logged = FALSE)

Arguments

y

A numerical vector with the dependent variable.

x

A matrix with the data, where the rows denote the samples (and the two groups) and the columns are the variables. This must be a matrix with the categorical variables as numbers, starting from 1. Welch's F-test is performed for each variable.

logged

A boolean variable; it will return the logarithm of the pvalue if set to TRUE.

Details

For each categorical variable in the x matrix Welch's F test is performed. This is the opposie of ftests, where there are many dependent variables and one categorical variable.

Value

A matrix with the test statistic and the p-value for each predictor variable.

Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and Manos Papadakis <papadakm95@gmail.com>.

References

Draper, N.R. and Smith H. (1988). Applied regression analysis. New York, Wiley, 3rd edition.

McCullagh, Peter, and John A. Nelder. Generalized linear models. CRC press, USA, 2nd edition, 1989.

See Also

regression, ftests, allbetas, correls

Examples

y <-  rnorm(100)
x <- matrix( rbinom(100 * 50, 2, 0.5) + 1 , ncol = 50)  
a <- colanovas(y, x)
x <- NULL

Rfast documentation built on March 18, 2022, 7:41 p.m.