var_rsc: Computes variance of latent traits and the one-parameter RSC...

Description Usage Arguments Value

Description

Computes variance of latent traits and the one-parameter RSC model for a combined assessment. #' @param resp a data.frame containing the binary item responses of both the individual assessment and the (conjunctively scored) group assessment. See details of rsc for information on formatting.

Usage

1
2
var_rsc(resp, u, parms, theta1, theta2, method = "MAP", obs = F,
  sigma = 3)

Arguments

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 of rsc for information on formatting.

theta1

the latent trait of member 1.

theta2

the latent trait of member 2.

method

one of c("ML", "MAP"). The latter isrecommended.

obs

logical: should standard errors be computed using the observed (TRUE) or expected (FALSE) Hessian?

sigma

prior standard deviation for logit of weight.

Value

3 * K by 3 * K covariance matrix of the parameter estimates, with K = length(u) and rows/cols ordered as rep(c(u_k, theta1_k, theta2_k), times = K).


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