dgirf_p {lazy.girt} R Documentation

## Calculation of the Derivative of Item Response Function with respect to Item Parameters

### Description

Calculation of the Derivative of Item Response Function with respect to Item Parameters

### Usage

```dgirf_p(paramj, thetaphi = NULL, weight = NULL, smallP = 0, DinP = 1,
thmin = -4, thmax = 4, npointth = 21, phmin = 0, phmax = 5,
npointph = 5, Pj = NULL, PPj = NULL, zero = 0, cat.first = 0,
log = 0, print = 0)
```

### Arguments

 `paramj` item parameters data frame for ONE item `weight` Weight data frame: NOT used. `smallP` Minimum value of probability `DinP` = 1 to include D=1.7 in logistic function `thmin` Minimum value of discrete thata value `thmax` Maximum value of discrete thata value `Pj` icrf: npoints x (ncatj-1) (no zero category) or NULL `PPj` icbrf of the Graded Response Model or NULL `zero` = 1 to include the xzero-th category in output `cat.first` = 1 to chage the category fist in the rows of Jack. `log` = 1 to obtain the log Jacobian: d log(ICRF) d param `print` = 1 to print result `theta` Discrete theta values `npoints` # of discrete points for theta

### Value

list of (Jack, Pj, PPj)
Jack (length(theta) x (ncatj-1)) x ncatj
derivative of vec(Pj) with respect to (a, b1, b2, ...)
If cat.first = 0
theta changes first, then k changes from 1 to ncatj
If cat.first = 1, category(k) changes first, then theta.
PPj will be output when type="G".

### Examples

```res=dirf_p( paramS1[3,], npoints=5, print=1 )
res=dirf_p( paramS1[3,], npoints=5, print=1, zero=1 )
res=dirf_p( paramS1[3,], npoints=5, print=1, cat.first=1 )

```

[Package lazy.girt version 0.1.3 Index]