Create a dichotomous response model
For slope vector a, intercept c, pseudo-guessing parameter g, upper bound u, and latent ability vector theta, the response probability function is
P(pick=0|a,c,g,u,th) = 1-P(pick=1|a,c,g,u,th)
P(pick=1|a,c,g,u,th) = g+(u-g)/(1+exp(-(a th + c)))
rpf.drm(factors = 1, multidimensional = TRUE, poor = FALSE)
factors |
the number of factors |
multidimensional |
whether to use a multidimensional model.
Defaults to |
poor |
if TRUE, use the traditional parameterization of the 1d model instead of the slope-intercept parameterization |
The pseudo-guessing and upper bound parameter are specified in
logit units (see logit).
For discussion on the choice of priors see Cai, Yang, and Hansen (2011, p. 246).
an item model
Cai, L., Yang, J. S., & Hansen, M. (2011). Generalized Full-Information Item Bifactor Analysis. Psychological Methods, 16(3), 221-248.
spec <- rpf.drm() rpf.prob(spec, rpf.rparam(spec), 0)
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