bayes.wcpm: Bayes function when running mcem with mcmc setting
In kamataak/orfr: The Model-based Approach to ORF Assessment Data

bayes.wcpm

R Documentation

Bayes function when running mcem with mcmc setting

Description

Bayes function when running mcem with mcmc setting

Usage

bayes.wcpm(
  calib.data = NA,
  stu.data = NA,
  studentid = NULL,
  passageid = NULL,
  season = NULL,
  grade = NULL,
  numwords.p = NULL,
  wrc = NULL,
  time = NULL,
  cases = NULL,
  external = NULL,
  parallel = T,
  n.chains = NA,
  iter = NA,
  burn = NA,
  thin = 1
)

Arguments

`calib.data`	- mcem class object
`stu.data`	- student reading data
`studentid`	The column name in the data that represents the unique student identifier.
`passageid`	The column name in the data that represents the unique passage identifier.
`season`	The column name in the data that represents the period of data collection.
`grade`	The column name in the data that represents the grade of student.
`numwords.p`	The column name in the data that represents the number of words in a passage.
`wrc`	The column name in the data that represents the words read correctly for each case.
`time`	The column name in the data that represents the time, in seconds, for each case.
`cases`	- student id vectors, will directly use passage data if no calib.data provided
`external`	- if not NULL, will use not student read passages for estimating
`parallel`	parallel=T, #logical, run in parallel? "T" or "F"
`n.chains`	int., number of the chains
`iter`	int., number of the iterations after the burn-in period
`burn`	int., number of the burn-in iteration
`thin`	int, thinning interval, a.k.a, period of saving samples