mirt: expand.table – R documentation

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expand.table

Expand summary table of patterns and frequencies

Description

The expand.table function expands a summary table of unique response patterns to a full sized data-set. By default the response frequencies are assumed to be on rightmost column of the input data, though this can be modified.

Usage

expand.table(tabdata, freq = colnames(tabdata)[ncol(tabdata)], sample = FALSE)

Arguments

`tabdata`	An object of class `data.frame` or `matrix` with the unique response patterns and the number of frequencies in the rightmost column (though see `freq` for details on how to omit this column)
`freq`	either a character vector specifying the column in `tabdata` to be used as the frequency count indicator for each response pattern (defaults to the right-most column) or a integer vector of length `nrow(tabdata)` specifying the frequency counts. When using the latter approach the `tabdata` input should not include any information regarding the counts, and instead should only include the unique response patterns themselves
`sample`	logical; randomly switch the rows in the expanded table? This does not change the expanded data, only the row locations

Value

Returns a numeric matrix with all the response patterns.

Author(s)

Phil Chalmers rphilip.chalmers@gmail.com

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi: 10.18637/jss.v048.i06

Examples

data(LSAT7)
head(LSAT7) # frequency in right-most column
LSAT7full <- expand.table(LSAT7)
head(LSAT7full)
dim(LSAT7full)

# randomly switch rows in the expanded response table
LSAT7samp <- expand.table(LSAT7, sample = TRUE)
head(LSAT7samp)
colMeans(LSAT7full)
colMeans(LSAT7samp) #equal

#--------

## Not run: 
# Generate data from separate response pattern matrix and freq vector
# The following uses Table 2.1 from de Ayala (2009)
f <- c(691,2280,242,235,158,184,1685,1053,134,462,92,65,571,79,87,41,1682,702,
       370,63,626,412,166,52,28,15,2095,1219,500,187,40,3385)

pat <- matrix(c(
   0, 0, 0, 0, 0,
   1, 0, 0, 0, 0,
   0, 1, 0, 0, 0,
   0, 0, 1, 0, 0,
   0, 0, 0, 1, 0,
   0, 0, 0, 0, 1,
   1, 1, 0, 0, 0,
   1, 0, 1, 0, 0,
   0, 1, 1, 0, 0,
   1, 0, 0, 1, 0,
   0, 1, 0, 1, 0,
   0, 0, 1, 1, 0,
   1, 0, 0, 0, 1,
   0, 1, 0, 0, 1,
   0, 0, 1, 0, 1,
   0, 0, 0, 1, 1,
   1, 1, 1, 0, 0,
   1, 1, 0, 1, 0,
   1, 0, 1, 1, 0,
   0, 1, 1, 1, 0,
   1, 1, 0, 0, 1,
   1, 0, 1, 0, 1,
   1, 0, 0, 1, 1,
   0, 1, 1, 0, 1,
   0, 1, 0, 1, 1,
   0, 0, 1, 1, 1,
   1, 1, 1, 1, 0,
   1, 1, 1, 0, 1,
   1, 1, 0, 1, 1,
   1, 0, 1, 1, 1,
   0, 1, 1, 1, 1,
   1, 1, 1, 1, 1), ncol=5, byrow=TRUE)

colnames(pat) <- paste0('Item.', 1:5)
head(pat)

table2.1 <- expand.table(pat, freq = f)
dim(table2.1)


## End(Not run)

mirt

Multidimensional Item Response Theory

v1.33.2

GPL (>= 3)

Authors

Phil Chalmers [aut, cre] (<https://orcid.org/0000-0001-5332-2810>), Joshua Pritikin [ctb], Alexander Robitzsch [ctb], Mateusz Zoltak [ctb], KwonHyun Kim [ctb], Carl F. Falk [ctb], Adam Meade [ctb], Lennart Schneider [ctb], David King [ctb], Chen-Wei Liu [ctb], Ogreden Oguzhan [ctb]

Initial release