longitdata

Longitudinal observation on single variable from different observations. Observations arranged in a column as the patient with corresponding column of ID.

datasets

High dimensional longitudinal data analysis with Markov Chain Monte Carlo(MCMC).
Currently support mixed effect regression with or without missing observations by considering
covariance structures. It provides estimates by missing at random and missing not at random assumptions.
In this R package, we present Bayesian approaches that statisticians and clinical
researchers can easily use. The functions' methodology is based on the book "Bayesian Approaches in Oncology Using R and OpenBUGS" by
Bhattacharjee A (2020) <doi:10.1201/9780429329449-14>.

Atanu Bhattacharjee

longit

High Dimensional Longitudinal Data Analysis Using MCMC

Akash Pawar

Bhrigu Kumar Rajbongshi

longitdata function

A <code>tibble</code> with 2 columns which are :<dl class="dl-horizontal">
<dt>ID</dt><dd>Patient ID</dd>
<dt>y</dt><dd>Repeated observations on the patient arranged in a row as per a subject</dd></dl>

Format

Repeatedly measured protein expression data — longitdata

A <code>tibble</code> with 2 columns which are :<dl class='dl-horizontal'>
<dt>ID</dt><dd>Patient ID</dd>
<dt>y</dt><dd>Repeated observations on the patient arranged in a row as per a subject</dd></dl>

longitdata: Repeatedly measured protein expression data

Description

Usage

Arguments

Format