StabCont: parameter stability test for continuous partitioning variable

In LongCART: Recursive Partitioning for Longitudinal Data and Right Censored Data Using Baseline Covariates

parameter stability test for continuous partitioning variable

Description

Performs parameter stability test (Kundu and Harezlak, 2019) with continuous partitioning variable to determine whether the parameters of linear mixed effects model remains same across all distinct values of given continuous partitioning variable.

Usage

StabCont(data, patid, fixed, splitvar)

Arguments

data	name of the dataset. It must contain variable specified for patid (indicating subject id) and all the variables specified in the formula and the StabCont(data, fixed, splitvar)partitioning variable of interest specified in splitvar.
patid	name of the subject id variable.
fixed	a two-sided linear formula object describing the fixed-effects part of the model, with the response on the left of a ~ operator and the terms, separated by + operators, on the right. Model with -1 to the end of right side indicates no intercept. For model with no fixed effect beyond intercept, please specify only 1 right to the ~ operator.
splitvar	the continuous partitioning variable of interest. It's value should not change over time.

Details

The continuous partitioning variable of interest. It's value should not change over time.

Y_i(t)= W_i(t)theta + b_i + epsilon_{it}

where W_i(t) is the design matrix, theta is the parameter associated with W_i(t) and b_i is the random intercept. Also, epsilon_{it} ~ N(0,sigma ^2) and b_i ~ N(0, sigma_u^2). Let X be the baseline continuous partitioning variable of interest. StabCont() performs the following omnibus test

H_0:theta_{(g)}=theta_0 vs. H_1: theta_{(g)} ^= theta_0, for all g

where, theta_{(g)} is the true value of theta for subjects with X=C_g where C_g is the any value realized by X.

Value

p	It returns the p-value for parameter instability test

Author(s)

Madan Gopal Kundu [e-mail]

References

Kundu, M. G., and Harezlak, J. (2019). Regression trees for longitudinal data with baseline covariates. Biostatistics & Epidemiology, 3(1):1-22.

See Also

StabCont, LongCART, plot, text

Examples

#--- Get the data
data(ACTG175)
               
#--- Run StabCont()                
out<- StabCont(data=ACTG175, patid="pidnum", fixed=cd4~time, splitvar="age")
out$pval

LongCART documentation built on May 18, 2022, 1:06 a.m.