Get an sspLNIRT.object from the precomputed sspLNIRT data

The function gets the sspLNIRT object from the sspLNIRT data tibble, containing the minimum sample size to reach the threshold of root mean squared errors (RMSE) of estimated parameters. The sspLNIRT data was precomputed using `optim_sample`. The RMSE is based on simulated data under the Joint Hierarchical Model using a 2-pl normal ogive model for response accuracy and a 3-pl log-normal model for response time.

Usage

get_sspLNIRT(thresh, out.par, K, mu.alpha, meanlog.sigma2, rho)

Arguments

thresh: Numeric vector. The desired RMSE threshold(s) of the target parameter(s) to be achieved.
out.par: Character vector. The name(s) of the target parameter(s) for the threshold(s).
K: Integer. The test length.
mu.alpha: Numeric. The mean of the discrimination parameter alpha.
meanlog.sigma2: Numeric. The meanlog of sigma2.
rho: Numeric. The correlation between theta and zeta.

Value

A list containing:

object: The sspLNIRT.object with results.
design: The design i.e., set of parameter values used for this result.

Examples

if (FALSE) { # \dontrun{
result <- get_sspLNIRT(
  thresh = c(.1, .05, .1, .05),
  out.par = c("alpha","phi", "beta", "lambda"),
  K = 10,
  mu.alpha = 1,
  meanlog.sigma2 = log(.6),
  rho = 0.2
)
summary(result$object)
result$cfg
} # }