summary.lsirm {lsirm12pl}

Summary the result of LSIRM

Description

summary is used to summary the result of LSIRM.

Usage

## S3 method for class 'lsirm'
summary(object, chain.idx = 1, estimate = "mean", CI = 0.95, ...)

Arguments

object

Object of class lsirm.

chain.idx

Numeric; Index of MCMC chain. Default is 1.

estimate

Character; Specifies the type of posterior estimate to provide for beta parameters. Options are "mean", "median", or "mode". Default is "mean".

CI

Numeric; The significance level for the highest posterior density interval (HPD) for the beta parameters. Default is 0.95.

...

Additional arguments.

Value

summary.lsirm contains following elements. A print method is available.

call

R call used to fit the model.

coef

Covariate coefficients posterior means.

mcmc.opt

The number of mcmc iteration, burn-in periods, and thinning intervals.

map.inf

Value of log maximum a posterior and iteration number which have log maximum a posterior.

BIC

Numeric value with the corresponding Bayesian information criterion (BIC).

method

Which model is fitted.

missing

The assumed missing type. One of NA, "mar" and "mcar".

dtype

Type of input data (Binary or Continuous).

ss

Whether a model selection approach using the spike-slab prior is applied.

Examples

# generate example item response matrix
data     <- matrix(rbinom(500, size = 1, prob = 0.5),ncol=10,nrow=50)

# 1PL LSIRM object
lsirm_result <- lsirm(data ~ lsirm1pl())
summary(lsirm_result)