Description Usage Arguments Details Value Author(s) References See Also Examples
This function returns the Jeffreys prior for an IRT model in the form of a density function, and optionally the normalizing constant of that prior.
1 |
ltm.obj |
An object representing an IRT model of a set of items, from the ltm package (e.g., using the |
inf.mat |
A two-column matrix representing the information function evaluated at a set of latent trait values, with the first column being the latent trait values and the second column the information at each value (e.g., as returned by the ltm |
inf.func |
An information function; a function taking a latent trait value and returning the information at that value. |
return |
The value(s) to be returned. "prior" returns the prior as a function; "nc" returns the normalizing constant; "both" returns both as a list. |
spl.method |
A |
range.int |
The range to integrate over in calculating the normalizing constant. |
Only one of ltm.obj, inf.mat, or inf.function should be supplied. An inf.mat matrix can be obtained using the plot function in the ltm package, with the options type="IIC", item=0, and plot=F. As the information function must be interpolated when inf.mat is supplied (using splinefun
), supplying an ltm object or information function directly will generally be more accurate. If inf.mat is supplied, the information should be evaluated at a large number of points over a wide range, to maintain accuracy.
Note that currently, range.int must be within (-10, 10) for grm
and gpcm
objects. If a grm
or gpcm
object is supplied and range.int is outside this range, the range will be reset.
If return="prior", the default, a function taking a latent trait value and returning the Jeffreys prior density at that point. If return="nc", the normalizing constant used to calculate the Jeffreys prior and also the lower bound to the Lindley information. If return="both", a list having the following structure:
prior |
The Jeffreys prior density as a function. |
nc |
The normalizing constant. |
Kristian E. Markon
Markon, K. E. (2013). Information utility: Quantifying the total psychometric information provided by a measure. Psychological Methods, 18, 15-35. doi: 10.1037/a0030638..
rJeffreys
, which randomly generates latent trait values distributed asccording to a Jeffreys prior density, and iota
and iota.c
, which calculate Lindley information quantities, possibly using the Jeffreys prior. Also see splinefun
, ltm
, grm
, and gpcm
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # using an ltm object
ltm.lsat <- ltm(LSAT~z1, IRT=FALSE)
jp.lsat <- Jeffreys(ltm.lsat)
jp.lsat(0)
# using inf.mat
inf.lsat <- plot(ltm.lsat, type="IIC", item=0, plot=FALSE, z=seq(-15, 15, length=10000))
jp.lsat <- Jeffreys(inf.mat=inf.lsat)
jp.lsat(0)
# returning normalizing constant
Jeffreys(ltm.lsat, return="nc")
Jeffreys(inf.mat=inf.lsat, return="nc")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.