visual_mc {diffcor}

Visualization of the simulated parameters

Description

To evaluate the quality of the Monte Carlo simulation beyond bias and coverage parameters (Muthén & Muthén, 2002), it can be helpful to also inspect the simulated parameters visually. To this end, visual_mc() can be used to visualize the simulated parameters (including corresponding confidence intervals) in relation to the targeted parameter.

Usage

visual_mc(emp.r, n, alpha = .05, n.intervals = 100, seed = 1234)

Arguments

emp.r

Targeted correlation coefficient of the simulation.

n

An integer reflecting the sample size.

alpha

Type I error. Default is .05.

n.intervals

An integer reflecting the number of simulated parameters that should be visualized in the graphic. Default is 100.

seed

To make the results reproducible, a random seed is specified.

Value

A plot in which the targeted correlation coefficient is visualized with a dashed red line and the simulated correlation coefficients are visualized by black squares and confidence intervals (level depending on the specification made in the argument 'alpha').

Author(s)

Christian Blötner [e-mail]

References

Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling: A Multidisciplinary Journal, 9(4), 599–620. https://doi.org/10.1207/S15328007SEM0904_8

Examples

visual_mc(emp.r = .25,
                    n = 300,
                    alpha = .05,
                    n.intervals = 100,
                    seed = 1234)