BysmxDIC {longit} | R Documentation |
Bayesian mixed effect model for high dimensional longitduinal data with deviance information criterion (DIC).
Description
Bayesian mixed effect model with random intercept and slopes provides inference with deviance information criterion (DIC). Data longitudinally measured missing value and having batched information. Fits using MCMC on longitudinal data set
Usage
BysmxDIC(m, tmax, t, group, chains, iter, out, data)
Arguments
m |
Starting number of column from where repeated observations begin |
tmax |
Ending number of columns till where the repeated observations ends |
t |
Timepoint information on which repeadted observations were taken |
group |
A categorical variable either 0 or 1. i.e. Gender - 1 male and 0 female |
chains |
Number of MCMC chains to be performed |
iter |
Number of iterations to be performed |
out |
DIC/HPD outcome |
data |
High dimensional longitudinal data |
Value
Gives posterior means, standard deviation.
Author(s)
Atanu Bhattacharjee, Akash Pawar and Bhrigu Kumar Rajbongshi
References
Bhattacharjee, A. (2020). Bayesian Approaches in Oncology Using R and OpenBUGS. CRC Press.
Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.
Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2012). Applied longitudinal analysis (Vol. 998). John Wiley & Sons.
Examples
##
data(msrep)
BysmxDIC(m=c(4,8,12),tmax=4,t="Age",group="Gender",chains=4,iter=1000,out="DIC",data=msrep)
##