Nstar: Multiplier term for second deriviative of log-likelihood of...
In peterhalpin/cirt: Psychometric models of small group collaborations

Description Usage Arguments Value

The Hessian of the log-likelihood of the RSC model a single item can be computed as M * hess_IRF - N * grad_IRF^2. This function computes (a matrix of values of) N. Called by functions that compute second derivatives of the log-likelihood.

1	Nstar(resp, u, parms, theta1, theta2, obs = T)

`resp`	a matrix or data.frame containing the (conjunctively-scored, binary)item responses.
`u`	the logit of the weight parameter of the RSC model.
`parms`	a data.frame with columns `parms$alpha` and `parms$beta` corresponding to the discrimination and difficulty parameters of the 2PL model, respectively.
`theta1`	the latent trait of member 1.
`theta2`	the latent trait of member 2.
`obs`	logical: should the observed value be returned? If not, the expected value is returned.