parameter stability test for continuous partitioning variable
parameter stability test for continuous partitioning variable
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.
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.
Yi(t)=Wi(t)theta+bi+epsilonit
where Wi(t) is the design matrix, theta is the parameter associated with Wi(t) and b_i is the random intercept. Also, epsilonitN(0,sigma2)
and biN(0,sigmau2). Let X be the baseline continuous partitioning variable of interest. StabCont() performs the following omnibus test
H0:theta(g)=theta0 vs. H1:theta(g)=theta0, for all g
where, theta(g) is the true value of theta for subjects with X=Cg
where Cg is the any value realized by X.
Returns
p: It returns the p-value for parameter instability test