Description Usage Arguments Value Examples
Estimate a test item parameters according to Item Response Theory.
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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 |
A list containing the estimates of the model parameters, the number of iterations, the loglikelihood final, the final values of the estimation procedure EM.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## 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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