This code is in reference to the paper: Kundu, D. and Das, K., 2024. "A quantile-regression approach to bivariate longitudinal joint modeling." Journal of Statistical Research 58(1) , pp : 111-130 , doi: 10.3329/jsr.v58i1.75417
(1) Data contour plot
(2) Convergence plot (to show parameter convergence)
(3) Longitudinal plot for the estimated qunatiles
(4) Estimated survival plots
(5) Parameter significance plots (based on 95% credible set).
Quantile_Vs_tau : shows no quantile crossing
Multi-normal_QQ_plot : serves as a motivation for joint modeling, citing deviation from bivariate normality
Contour : Shows the bivariate -density of mean responses across subjects.
Medicine : shows the estimate and 95% CI for the "betas" corresponding to the medicine in the longitudinal submodel across quantiles
Fixed_Var : Tile plot for showing significance of coefficients for each "fixed variable" across (submodel X quantile)
Association_Convergence : Plot showing convergence of the association parameter estimates (note: on an average Gelman-Rubin convergence stat < 1.1)
Association: shows the estimate and 95% CI for the "psis" corresponding to the medicine in the survival submodel across quantiles
Longitudinal : Estimated bi-variate longitudinal quantiles across time for various quantiles
Survival : Estimated non relapse probabilities for various quantiles