StabCat {LongCART} | R Documentation |
parameter stability test for categorical partitioning variable
Description
Performs parameter stability test (Kundu and Harezlak, 2019) with categorical partitioning variable to determine whether the parameters of linear mixed effects model remains same across all distinct values of given categorical partitioning variable.
Usage
StabCat(data, patid, fixed, splitvar)
Arguments
data |
name of the dataset. It must contain variable specified for |
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 |
splitvar |
the categorical partitioning variable of interest. It's value should not change over time. |
Details
The categorical 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 categorical partitioning
variable of interest. StabCat()
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 madan_g.kundu@yahoo.com
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
, LongCART
, LongCART
Examples
#--- Get the data
data(ACTG175)
#--- Run StabCat()
out<- StabCat(data=ACTG175, patid="pidnum", fixed=cd4~time, splitvar="gender")
out$pval