QQdiff {diffIRT} R Documentation

## Assessing diffIRT model fit for the response times using QQ-plots

### Description

This function plots the observed response times against the predicted response times for a `diffIRT` object.

### Usage

```QQdiff(object, items, plot=2, breaks=15, quant=NULL, maxRT=NULL)
```

### Arguments

 `object` A `diffIRT` object for which the QQ-plots need to be created. `items` A vector denoting for which items the QQ-plots need to be created. `plot` Integer; 1: only QQ-plots. 2: both a QQ-plot and a histogram containing the predicted and observed distribution. `breaks` Number of breaks to be used in hist when `plot`=2. `quant` The number of quantiles to be used. If `NULL`, the number of quantiles will equal the number of subjects. `maxRT` The maximum response time used in finding the quantiles of the theoretical distribution. If `NULL`, twice the maximum observed response time is used for each item. Increasing `maxRT` will increase computation time and should only be used when uniroot produces errors.

### Details

`QQdiff` calculates the predicted quantiles in the marginal response time distribution of the given model (D-diffusion or Q-diffusion).

### Value

Function `QQdiff` returns a list with entries:

 `qexp` a vector with predicted quantiles. `qobs` a vector with observed quantiles.

### Author(s)

Dylan Molenaar d.molenaar@uva.nl

### References

Navarro, D.J. & Fuss, I.G. (2009). Fast and accurate calculations for first-passagetimes in Wiener diffusion models. Journal of mathematical psychology, 53, 222-230.

Tuerlinckx, F., & De Boeck, P. (2005). Two interpretations of the discrimination parameter. Psychometrika, 70, 629-650.

van der Maas, H.L.J., Molenaar, D., Maris, G., Kievit, R.A., & Borsboom, D. (2011). Cognitive Psychology Meets Psychometric Theory: On the Relation Between Process Models for Decision Making and Latent Variable Models for Individual Differences. Psychological Review, 118, 339-356.

`diffIRT` for fitting diffusion IRT models. `factest` for estimation of factor scores (person drift rate and person boundary separation). `simdiff` for simulating data according to the D-diffusion or Q-diffusion IRT model.

### Examples

```## Not run:
# open rotation data
data(rotation)
x=rotation[,1:10]
rt=rotation[,11:20]

# fit an unconstrained Q-diffusion model
res1=diffIRT(rt,x,model="Q")

# make QQ-plots and histograms for items 1 to 4.
QQdiff(res1, items=1:4, plot=2, maxRT=rep(50,4))

## End(Not run)
```

[Package diffIRT version 1.5 Index]