Description Usage Arguments Details Value Author(s) References See Also Examples

This function applies the three-way analysis of variance with mixed classification for testing the Rasch model.

1 2 |

`data` |
A data frame in which the variables specified in the model will be found. Note that data needs to be in 'long' format. |

`group` |
Column name of the data frame containing the grouping variable. |

`person` |
Column name of the data frame containing the person number variable. |

`item` |
Column name of the data frame containing the item number variable. |

`response` |
Column name of the data frame containing the response variable. |

`output` |
If |

The F-test in a three-way analysis of variance design (A > **B**) x C with mixed classification
(fixed factor A = subgroup, random factor B = testees, and fixed factor C = items) is used
to test the Rasch model. Rasch model fitting means that there is no interaction A x C.
A statistically significant interaction A x C indicates differential item functioning (DIF)
of the items with respect of the two groups of testees Note, if a main effect of A (subgroup)
exists, an artificially high type I risk of the A x C interaction F-test results - that is,
the approach works as long as no statistically significant main effect of A occurs.
Note that in case of unbalanced groups computation can take a long time.

Returns an ANOVA table

Takuya Yanagida takuya.yanagida@univie.ac.at, Jan Steinfeld jan.steinfeld@univie.ac.at

Kubinger, K. D., Rasch, D., & Yanagida, T. (2009). On designing data-sampling for Rasch model
calibrating an achievement test. *Psychology Science Quarterly, 51*, 370-384.

Kubinger, K. D., Rasch, D., & Yanagida, T. (2011). A new approach for testing the Rasch model.
*Educational Research and Evaluation, 17*, 321-333.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
## Not run:
# simulate Rasch model based data
# 100 persons, 20 items,
dat <- simul.rasch(100, items = seq(-3, 3, length.out = 20))
# reshape simulated data into 'long' format with balanced assignment
# of testees into two subgroups
dat.long <- reshape.rasch(dat, group = rep(0:1, each = nrow(dat) / 2))
# apply three-way analysis of variance with mixed classification for testing the Rasch model
aov.rasch(dat.long)
# extract variable names of items
vnames <- grep("it", names(aid_st2), value = TRUE)
# reshape aid subtest 2 data into 'long' format with split criterium sex
aid_long.sex <- reshape.rasch(aid_st2[, vnames], group = aid_st2[, "sex"])
# apply three-way analysis of variance with mixed classification for testing the Rasch model
aov.rasch(aid_long.sex)
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.