dl_full: Gradient of the log-likelihood of a combined assessment.

In peterhalpin/cirt: Psychometric models of small group collaborations

Description

This function computes first derivatives of the log-likelihood for a combined assessment, in which the 2PL model is used for the individual component of the assessment and the one-parameter RSC model is used for the group component of the assessment. The derivatives are taken in c(u, theta1, theta2). See help(l_full) for details on formatting of resp and parms.

Usage

dl_full(resp, u, parms, theta1, theta2)

Arguments

resp	a data.frame containing the binary item responses of both the individual assessment and the (conjunctively scored) group assessment. See details for information on formatting.
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. See details for information on formatting.
theta1	the latent trait of member 1.
theta2	the latent trait of member 2.

Value

3 * K - vector of first derivatives, with K = length(u), ordered as rep(c(u_k, theta1_k, theta2_k), times = K).

peterhalpin/cirt documentation built on May 25, 2019, 1:50 a.m.