# helpers: Helper Functions In Rirt: Data Analysis and Parameter Estimation Using Item Response Theory

## Description

`model_polytomous_3dindex` creates indices extracting 3D stats

`model_polytomous_3dresponse` converts responses from 2D to 3D

`hermite_gauss` stores pre-computed hermite gaussian quadratures points and weights

`nr_iteration` updates the parameters using the Newton-Raphson method

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```model_polytomous_3dindex(u) model_polytomous_3dresponse(u) hermite_gauss(degree = c("20", "11", "7")) nr_iteration(param, free, dv, h_max, lr, bound) estimate_3pl_debug(tracking, k) estimate_3pl_eval(true_params, t, a, b, c, t_free, a_free, b_free, c_free) estimate_gpcm_debug(tracking, k) estimate_gpcm_eval(true_params, n_c, t, a, b, d, t_free, a_free, b_free, d_free) estimate_grm_debug(tracking, k) estimate_grm_eval(true_params, n_c, t, a, b, t_free, a_free, b_free) ```

## Arguments

 `u` the observed response, 2d matrix, values start from 0 `degree` the degree of hermite-gauss quadrature: '20', '11', '7' `param` the parameter being estimated `free` TRUE to free parameters, otherwise fix parameters `dv` the first and second derivatives `h_max` the maximum value of h `lr` the learning rate `bound` the lower and upper bounds of the parameter `tracking` estimation tracking information `k` the number of iterations in estimation `true_params` a list of true parameters `t` estimated ability parameters `a` estimated discrimination parameters `b` estimated difficulty parameters `c` estimated guessing parameters `t_free` TRUE to estimate ability parameters, otherwise fix `a_free` TRUE to estimate discrimination parameters, otherwise fix `b_free` TRUE to estimate difficulty parameters, otherwise fix `c_free` TRUE to estimate guessing parameters, otherwise fix

Rirt documentation built on Oct. 30, 2019, 12:13 p.m.