% File src/library/stats/man/ansari.test.Rd % Part of the R package, https://www.R-project.org % Copyright 1995-2018 R Core Team % Distributed under GPL 2 or later \name{ansari.test} \alias{ansari.test} \alias{ansari.test.default} \alias{ansari.test.formula} \title{\I{Ansari}-\I{Bradley} Test} \description{ Performs the \I{Ansari}-\I{Bradley} two-sample test for a difference in scale parameters. } \usage{ ansari.test(x, \dots) \method{ansari.test}{default}(x, y, alternative = c("two.sided", "less", "greater"), exact = NULL, conf.int = FALSE, conf.level = 0.95, \dots) \method{ansari.test}{formula}(formula, data, subset, na.action, \dots) } \arguments{ \item{x}{numeric vector of data values.} \item{y}{numeric vector of data values.} \item{alternative}{indicates the alternative hypothesis and must be one of \code{"two.sided"}, \code{"greater"} or \code{"less"}. You can specify just the initial letter.} \item{exact}{a logical indicating whether an exact p-value should be computed.} \item{conf.int}{a logical,indicating whether a confidence interval should be computed.} \item{conf.level}{confidence level of the interval.} \item{formula}{a formula of the form \code{lhs ~ rhs} where \code{lhs} is a numeric variable giving the data values and \code{rhs} a factor with two levels giving the corresponding groups.} \item{data}{an optional matrix or data frame (or similar: see \code{\link{model.frame}}) containing the variables in the formula \code{formula}. By default the variables are taken from \code{environment(formula)}.} \item{subset}{an optional vector specifying a subset of observations to be used.} \item{na.action}{a function which indicates what should happen when the data contain \code{NA}s. Defaults to \code{getOption("na.action")}.} \item{\dots}{further arguments to be passed to or from methods.} } \details{ Suppose that \code{x} and \code{y} are independent samples from distributions with densities \eqn{f((t-m)/s)/s} and \eqn{f(t-m)}, respectively, where \eqn{m} is an unknown nuisance parameter and \eqn{s}, the ratio of scales, is the parameter of interest. The \I{Ansari}-\I{Bradley} test is used for testing the null that \eqn{s} equals 1, the two-sided alternative being that \eqn{s \ne 1}{s != 1} (the distributions differ only in variance), and the one-sided alternatives being \eqn{s > 1} (the distribution underlying \code{x} has a larger variance, \code{"greater"}) or \eqn{s < 1} (\code{"less"}). By default (if \code{exact} is not specified), an exact p-value is computed if both samples contain less than 50 finite values and there are no ties. Otherwise, a normal approximation is used. Optionally, a nonparametric confidence interval and an estimator for \eqn{s} are computed. If exact p-values are available, an exact confidence interval is obtained by the algorithm described in Bauer (1972), and the \I{Hodges}-\I{Lehmann} estimator is employed. Otherwise, the returned confidence interval and point estimate are based on normal approximations. Note that mid-ranks are used in the case of ties rather than average scores as employed in \bibcite{Hollander & Wolfe (1973)}. See, e.g., \bibcite{Hajek, Sidak and Sen (1999), pages 131ff}, for more information. } \value{ A list with class \code{"htest"} containing the following components: \item{statistic}{the value of the \I{Ansari}-\I{Bradley} test statistic.} \item{p.value}{the p-value of the test.} \item{null.value}{the ratio of scales \eqn{s} under the null, 1.} \item{alternative}{a character string describing the alternative hypothesis.} \item{method}{the string \code{"Ansari-Bradley test"}.} \item{data.name}{a character string giving the names of the data.} \item{conf.int}{a confidence interval for the scale parameter. (Only present if argument \code{conf.int = TRUE}.)} \item{estimate}{an estimate of the ratio of scales. (Only present if argument \code{conf.int = TRUE}.)} } \note{ To compare results of the \I{Ansari}-\I{Bradley} test to those of the F test to compare two variances (under the assumption of normality), observe that \eqn{s} is the ratio of scales and hence \eqn{s^2} is the ratio of variances (provided they exist), whereas for the F test the ratio of variances itself is the parameter of interest. In particular, confidence intervals are for \eqn{s} in the \I{Ansari}-\I{Bradley} test but for \eqn{s^2} in the F test. } \references{ David F. Bauer (1972). Constructing confidence sets using rank statistics. \emph{Journal of the American Statistical Association}, \bold{67}, 687--690. \doi{10.1080/01621459.1972.10481279}. Jaroslav Hajek, Zbynek Sidak and Pranab K. Sen (1999). \emph{Theory of Rank Tests}. San Diego, London: Academic Press. Myles Hollander and Douglas A. Wolfe (1973). \emph{Nonparametric Statistical Methods}. New York: John Wiley & Sons. Pages 83--92. } \seealso{ \code{\link{fligner.test}} for a rank-based (nonparametric) \eqn{k}-sample test for homogeneity of variances; \code{\link{mood.test}} for another rank-based two-sample test for a difference in scale parameters; \code{\link{var.test}} and \code{\link{bartlett.test}} for parametric tests for the homogeneity in variance. \code{\link[coin:ScaleTests]{ansari_test}} in package \CRANpkg{coin} for exact and approximate \emph{conditional} p-values for the \I{Ansari}-\I{Bradley} test, as well as different methods for handling ties. } \examples{ ## Hollander & Wolfe (1973, p. 86f): ## Serum iron determination using Hyland control sera ramsay <- c(111, 107, 100, 99, 102, 106, 109, 108, 104, 99, 101, 96, 97, 102, 107, 113, 116, 113, 110, 98) jung.parekh <- c(107, 108, 106, 98, 105, 103, 110, 105, 104, 100, 96, 108, 103, 104, 114, 114, 113, 108, 106, 99) ansari.test(ramsay, jung.parekh) ansari.test(rnorm(10), rnorm(10, 0, 2), conf.int = TRUE) ## try more points - failed in 2.4.1 ansari.test(rnorm(100), rnorm(100, 0, 2), conf.int = TRUE) } \keyword{htest}