| Bysmxmss {longit} | R Documentation |
Bayesian mixed model with random intercepts and random slopes for high dimensional longitudinal data with batch size.
Description
Bayesian mixed effect model with random intercept and slopes. Data longitudinally measured missing value and having batched information. Fits using MCMC on longitudinal data set
Usage
Bysmxmss(m, tmax, timepoints, group, chains, iter, data)
Arguments
m |
Starting number of column from where repeated observations begin |
tmax |
Maximum batch of visits considered as repeated measurements |
timepoints |
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 |
data |
High dimensional longitudinal data |
Value
Gives posterior means, standard deviation.
Author(s)
Atanu Bhattacharjee and Akash Pawar
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
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data(repdat)