Nothing
### permutation test without transformations
oneway_test <- function(object, ...) UseMethod("oneway_test")
oneway_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("oneway_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
oneway_test.IndependenceProblem <- function(object, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
TRUE
}
)
## convert factors to ordered and attach scores if requested
if (!is.null(args$scores)) {
object <- setscores(object, args$scores)
args$scores <- NULL
}
## set test statistic to scalar for linear-by-linear and two-sample tests
args$teststat <- if (is_ordered_x(object) || twosamp) "scalar"
else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (is_ordered_x(object@statistic))
object@method <- "Linear-by-Linear Association Test"
else if (twosamp) {
object@method <- "Two-Sample Fisher-Pitman Permutation Test"
object@nullvalue <- 0
} else
object@method <- "K-Sample Fisher-Pitman Permutation Test"
object
}
### OK, OK, here is the most prominent one ...
wilcox_test <- function(object, ...) UseMethod("wilcox_test")
wilcox_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("wilcox_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
wilcox_test.IndependenceProblem <- function(object,
conf.int = FALSE, conf.level = 0.95, ...) {
args <- setup_args(
teststat = "scalar",
ytrafo = function(data)
trafo(data, numeric_trafo = rank_trafo),
check = function(object) {
if (!is_2sample(object))
stop(sQuote("object"),
" does not represent a two-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
TRUE
}
)
object <- do.call("independence_test", c(list(object = object), args))
object@method <- "Wilcoxon-Mann-Whitney Test"
object@nullvalue <- 0
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "location", level = level),
conf.level = conf.level)
object
}
### Kruskal-Wallis test
kruskal_test <- function(object, ...) UseMethod("kruskal_test")
kruskal_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("kruskal_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
kruskal_test.IndependenceProblem <- function(object, ...) {
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = rank_trafo),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
TRUE
}
)
## convert factors to ordered and attach scores if requested
if (!is.null(args$scores)) {
object <- setscores(object, args$scores)
args$scores <- NULL
}
## set test statistic to scalar for linear-by-linear tests
args$teststat <- if (is_ordered_x(object)) "scalar"
else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (is_ordered_x(object@statistic))
object@method <- "Linear-by-Linear Association Test"
else
object@method <- "Kruskal-Wallis Test"
object
}
### normal quantiles (van der Waerden) test
normal_test <- function(object, ...) UseMethod("normal_test")
normal_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("normal_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
normal_test.IndependenceProblem <- function(object,
ties.method = c("mid-ranks", "average-scores"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
normal_trafo(y, ties.method = ties.method)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
TRUE
}
)
## convert factors to ordered and attach scores if requested
if (!is.null(args$scores)) {
object <- setscores(object, args$scores)
args$scores <- NULL
}
## set test statistic to scalar for linear-by-linear and two-sample tests
args$teststat <- if (is_ordered_x(object) || twosamp) "scalar"
else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (is_ordered_x(object@statistic))
object@method <- "Linear-by-Linear Association Test"
else if (twosamp) {
object@method <- "Two-Sample van der Waerden (Normal Quantile) Test"
object@nullvalue <- 0
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "location", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample van der Waerden (Normal Quantile) Test"
object
}
### median test
median_test <- function(object, ...) UseMethod("median_test")
median_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("median_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
median_test.IndependenceProblem <- function(object,
mid.score = c("0", "0.5", "1"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
median_trafo(y, mid.score = mid.score)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
TRUE
}
)
## convert factors to ordered and attach scores if requested
if (!is.null(args$scores)) {
object <- setscores(object, args$scores)
args$scores <- NULL
}
## set test statistic to scalar for linear-by-linear and two-sample tests
args$teststat <- if (is_ordered_x(object) || twosamp) "scalar"
else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (is_ordered_x(object@statistic))
object@method <- "Linear-by-Linear Association Test"
else if (twosamp) {
object@method <- "Two-Sample Brown-Mood Median Test"
object@nullvalue <- 0
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "location", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Brown-Mood Median Test"
object
}
### Savage test
savage_test <- function(object, ...) UseMethod("savage_test")
savage_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("savage_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
savage_test.IndependenceProblem <- function(object,
ties.method = c("mid-ranks", "average-scores"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
savage_trafo(y, ties.method = ties.method)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
TRUE
}
)
## convert factors to ordered and attach scores if requested
if (!is.null(args$scores)) {
object <- setscores(object, args$scores)
args$scores <- NULL
}
## set test statistic to scalar for linear-by-linear and two-sample tests
args$teststat <- if (is_ordered_x(object) || twosamp) "scalar"
else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (is_ordered_x(object@statistic))
object@method <- "Linear-by-Linear Association Test"
else if (twosamp) {
object@method <- "Two-Sample Savage Test"
object@nullvalue <- 0
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "location", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Savage Test"
object
}
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