Estimate a test item parameters.

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Description

Estimate a test item parameters according to Item Response Theory.

Usage

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irtpp(dataset = NULL, model, dims = 1, initialvalues = NULL,
  filename = NULL, output = NULL, loglikflag = F,
  convergenceEpsilon = 1e-04)

Arguments

dataset

The matrix with the responses from the individuals.

model

The model used to calibrate the parameters.

dims

The dimensions to use on the estimation, remember to use the initial parameters if you want highquality estimation.

initialvalues

The matrix with the initial values for the optimization process.

filename

Optional argument specifying a CSV file to read instead of a dataset in memory.

output

Optional. Additonal arguments that need.

loglikflag

Optional. Show the loglikelihood at the end of estimation procedure. Also shows AIC and BIC statistic.

convergenceEpsilon

Optional. Convergence value, default value of 1E-4

Value

A list containing the estimates of the model parameters, the number of iterations, the loglikelihood final, the final values of the estimation procedure EM.

Examples

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## Simulation data for the model "1pl"
# data <- simulateTest(model = "1PL", items = 10, individuals = 500)
## Estimation of the parameters
# irtpp(dataset = data$test, model = "1PL")

## Simulation data for the model "2pl"
# data <- simulateTest(model = "2PL", items = 20, individuals = 800)
## Estimation of the parameters
# irtpp(dataset = data$test, model = "2PL")

## Simulation data for the model "3pl"
# data <- simulateTest(model = "3PL", items = 100, individuals = 1000)
## Estimation of the parameters
# irtpp(dataset = data$test, model = "3PL") 

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