Package 'jlst'

Joint location-and-scale test using Fisher's method

Description

jlsp performs the joint location-and-scale test using Fisher's method.

Usage

jlsp(y, x, covar = NULL, covar.var = FALSE, var.type = 1, x.sq = FALSE)

Arguments

y	vector of outcome values
x	vector of exposure values
covar	data.frame of covariates
covar.var	adjust the second stage (variance component) of the approach by the covariates
x.sq	include x-squared in the variance part of the model
type	type of test, where 1 = Breusch-Pagan variance test, and 2 = Brown-Forsythe variance test (default: 1)

Value

jlsp returns a list of results:

Q / F	the test statistic
DF	the degrees of freedom
P	the p-value

Author(s)

James Staley [email protected]

Examples

x <- rbinom(1000, 1, 0.5)
y <- 0.5 + 0.025 * x + rnorm(1000, 0, sqrt(0.005 * x)) + rnorm(1000, 0, 0.1)
jlsp(y, x, var.type = 2)

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Joint location-and-scale test

Description

jlssc performs the joint location-and-scale score test.

Usage

jlssc(y, x, covar = NULL, type = 1, x.sq = FALSE, x.reg = TRUE)

Arguments

y	vector of outcome values
x	vector of exposure values
covar	data.frame of covariates
type	type of test, where 1 = Breusch-Pagan variance test, 2 = Brown-Forsythe variance test, 3 = Method of moments version of test 1, and 4 = Method of moments version of test 2] (default: 1)
x.sq	include x-squared in the model
x.reg	regress out the covariates from the exposure terms

Value

jlst returns a data.frame of results:

Q	the test statistic
DF	the degrees of freedom
P	the p-value

Author(s)

James Staley [email protected]

Examples

x <- rbinom(1000, 1, 0.5)
y <- 0.5 + 0.025 * x + rnorm(1000, 0, sqrt(0.005 * x)) + rnorm(1000, 0, 0.1)
jlssc(y, x)

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Variability tests

Description

vartest performs variability tests by either the Breusch-Pagan or Brown-Forsythe methods.

Usage

vartest(y, x, covar = NULL, covar.var = FALSE, type = 1, x.sq = FALSE)

Arguments

y	vector of outcome values
x	vector of exposure values
covar	data.frame of covariates
covar.var	adjust the second stage (variance component) of the approach by the covariates
type	type of test, where 1 = Breusch-Pagan variance test, and 2 = Brown-Forsythe variance test (default: 1)
x.sq	include x-squared in the variance part of the model

Value

vartest returns a list of results:

coef	model coefficients from variance part of the model
test	data.frame of test results

• F: the test statistic

• DF: the degrees of freedom

• P: the p-value

Author(s)

James Staley [email protected]

Examples

x <- rbinom(1000, 1, 0.5)
y <- 0.5 + 0.025 * x + rnorm(1000, 0, sqrt(0.005 * x)) + rnorm(1000, 0, 0.1)
vartest(y, x, type = 2)

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