relvm: Multiple Estimation Of The Random Effect Latent Variable...

In huangrh/relvm: Random Effect Laten Variable Model For Hospital Compare

Multiple Estimation Of The Random Effect Latent Variable Model Parameters

Description

Estimate multiple measure groups of the random effect latent variable model

relvm.

Usage

relvm(object, groups = NULL, fit = list(inits = NULL, use_wt = c("step2")),
  file = NULL)

Arguments

object	A mstbl object.
groups	A vector of measure group names. The default is NULL, in which case a vector of all groups will be generated accordingly.
fit	A list of fitting parameters. init: Initial values for mu, fl, and err term in a data frame. fl is the factor loading. They will be initialized generally if it is null. The default is zero for mu and one for the rest. predict: The default is TRUE, which calculate the group score for each hospital. use_wt: A vector of strings, eg. c("step1", "step2"), corresponding to step 1 (optimize the model parameters) and step 2 (predict the group score) in the latent variable model, respectively. For example, fit = list(use_wt = "step2") tells the program to ignore the weight in step 1 and only use the weight in step 2.
file	File name in a rds format to cache the results on hard drive.

Value

An list of S3 object of class "relvms" with estimated parametes.

See Also

mstbl

Examples

# require(rstarating)
# To fit just one group: 'outcome_mort'
fit <- relvm(mstbl(cms_star_rating_input_2017dec),groups="outcome_mort")

# use weight in step 2 only (by default, weigt are used in step 1 and step 2)
fit <- relvm(mstbl(cms_star_rating_input_2017dec),groups="outcome_mort", fit=list(use_wt="step2"))

# Use weight in step 1 only (for test purpose only).
fit <- relvm(mstbl(cms_star_rating_input_2017dec),groups="outcome_mort", fit=list(use_wt="step1"))

huangrh/relvm documentation built on Nov. 1, 2024, 9:01 p.m.