dl_RSC: Gradient of log-likelihood of one-parameter RSC model.

In peterhalpin/BearShare: Psychometric models of small group collaborations

Description

Computes the first derivatives of the log-likelihood, in c(u, theta1, theta2). Called by rsc.

Usage

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

Arguments

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.

Value

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

peterhalpin/BearShare documentation built on May 25, 2019, 12:48 a.m.