test.bootwrq: Test of covariate effects between different quantiles
In weightQuant: Weights for Incomplete Longitudinal Data and Quantile Regression

Description Usage Arguments Details Value Author(s)

View source: R/test.bootwrq.R

This function provides a test for the covariate effects estimated for different quantiles.

1	test.bootwrq(x, m)

`x`	results from bootstrap estimations obtained with bootwrq function
`m`	a quantile regression model estimated with rq function from quantreg package. At least 2 quantiles should be specified in rq function.

For 2 quantiles tau1 and tau2, the test of the null hypothesis H0 : b_tau1 = b_tau2 is obtained with the following procedure : 1. estimate the difference diff = b_tau1 - b_tau2 on the initial sample (ie from model m) 2. estimate the difference diff_b = b_tau1^b - b_tau2^b on each of the B bootstrap samples 3. compute se_diff, the empirical standard error of these B differences 4. the associated p-value is obtained with the Gaussian assumption ( p-value = 2*P(N(0,1) > abs(diff/se_diff)) )

A list containing :

`results0`	a matrix with 3 columns containing the results (difference of the coefficients, standard erros of the diffrence and assocated p-values) without computing the weights in each bootstrap sample. Or NULL if the bootstrap results are obtained with wcompute=1.
`results1`	a matrix with 3 columns containing the results (difference of the coefficients, standard erros of the diffrence and assocated p-values) with re-estimated weights on each bootstrap sample. Or NULL if the bootstrap results are obtained with wcompute=0.

Viviane Philipps

weightQuant documentation built on Jan. 5, 2022, 5:08 p.m.