robcat (version 0.2)

polycor_mle: Maximum likelihood estimation of polychoric correlation coefficient

Description

Implements the maximum likelihood estimator of Olsson (1979, Psychometrika, tools:::Rd_expr_doi("10.1007/BF02296207")) for the polychoric correlation model.

Usage

polycor_mle(
  x,
  y = NULL,
  variance = TRUE,
  constrained = "ifneeded",
  twostep = FALSE,
  method = NULL,
  maxcor = 0.999,
  tol_thresholds = 0.01,
  init = initialize_param(x, y)
)

Value

An object of class "robpolycor". See polycor() for details.

Arguments

x

Vector of integer-valued responses to first item, or contingency table (a "table" object).

y

Vector of integer-valued responses to second item; only required if x is not a contingency table.

variance

Shall an estimated asymptotic covariance matrix be returned? Default is TRUE.

constrained

Shall strict monotonicity of thresholds be explicitly enforced by linear constraints? This can be a logical (TRUE or FALSE), or "ifneeded" to first try unconstrained optimization and in case of an error perform constrained optimization. Default is "ifneeded".

twostep

Shall two-step estimation of Olsson (1979) <doi:10.1007/BF02296207> be performed? Default is FALSE.

method

Numerical optimization method, see optim() and constrOptim(). Default is to use "L-BFGS-B" in case of unconstrained optimization and "Nelder-Mead" in case of constrained optimization.

maxcor

Maximum absolute correlation (to ensure numerical stability). Default is 0.999.

tol_thresholds

Minimum distance between consecutive thresholds (to enforce strict monotonicity); only relevant in case of constrained optimization. Default is 0.01.

init

Initialization of numerical optimization. Default is neutral.

Examples

## example data
set.seed(123)
x <- sample(c(1,2,3), size = 100, replace = TRUE)
y <- sample(c(1,2,3), size = 100, replace = TRUE)

polycor(x,y)     # robust
polycor_mle(x,y) # non-robust MLE