DFfun | R Documentation |

DFfun computes the first and second derivatives of the negative log likelihoods for a set of examinees. Items can be either binary or multi-option. The analysis is within the closed interval [0,100].

```
DFfun(index, SfdList, chcemat)
```

`index` |
Initial values for score indices in [0,n]/[0,100]. Vector of size N. |

`SfdList` |
A numbered list object produced by a TestGardener analysis of
a test. Its length is equal to the number of items in the test or questions
in the scale. Each member of |

`chcemat` |
An |

A named list for results `DF`

and `D2F`

:

`DF:` |
First derivatives of the negative log likelihood values, vector of size N |

`D2F:` |
Second derivatives of the negative log likelihood values, vector of size N |

Juan Li and James Ramsay

Ramsay, J. O., Li J. and Wiberg, M. (2020) Full information optimal scoring. Journal of Educational and Behavioral Statistics, 45, 297-315.

Ramsay, J. O., Li J. and Wiberg, M. (2020) Better rating scale scores with information-based psychometrics. Psych, 2, 347-360.

```
make_dataList,
index_fun,
Ffun,
Ffuns_plot
```

```
# Example 1:
# Compute the first and second derivative values of the objective function
# for locating each examinee for the 24-item short form of the
# SweSAT quantitative test on the percentile score index continuum.
# Use only the first five examinees.
chcemat <- Quant_13B_problem_dataList$chcemat
SfdList <- Quant_13B_problem_parmList$SfdList
index <- Quant_13B_problem_parmList$index
DFfunResult <- DFfun(index[1:5], SfdList, chcemat[1:5,])
DFval <- DFfunResult$DF
D2Fval <- DFfunResult$D2F
```

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