FedIRT (version 1.1.0)

fedirt: Federated IRT model

Description

This function combines all types of algorithm of federated IRT models. It inputs a dataset and return the estimated IRT parameters.

Usage

fedirt(inputdata, model_name = "2PL", school_effect = FALSE, federated = "Avg")

Value

Corresponding model result as a list.

Arguments

inputdata

A list of all responding matrices.

model_name

The name of the model you want to use. Can be "1PL" "2PL" or "graded". "1PL" refers to Rasch Model, "2PL" refers to two-parameter logistic model, "graded" refers to graded model.

school_effect

A bool parameter, TRUE refers to considering the school effect as a fixed effect. Default is FALSE.

federated

The federated learning method. Default is "Avg", meaning using Federated Average. Can also be "Med", meaning Federated Median.

Details

Input is a list of responding matrices from each school, every responding matrix is one site's data.

Examples

if (FALSE) {
# turn input data to a list
inputdata = list(as.matrix(example_data_2PL))
# Call fedirt() function, and use 2PL model with school effect as a fixed effect
fedresult = fedirt(inputdata, model_name = "2PL",school_effect = TRUE)

# turn input data to a list
inputdata = list(as.matrix(example_data_2PL_1), as.matrix(example_data_2PL_2))
# Call fedirt() function, and use graded model
fedresult = fedirt(inputdata, model_name = "graded")
}