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.