Legacy simulation of item-sort target-count power — simulate_csv

Auxiliary compatibility helper. It estimates by simulation the power of the exact target-count test of Howard and Melloy (2016). For supported exact planning, prefer sort_power(), which does not require Monte Carlo simulation.

Usage

simulate_csv_power(N = 20, true_p = 0.65, reps = 2000, alpha = 0.05)

Arguments

N: Number of judges per item.
true_p: True assignment probability to the target construct.
reps: Number of simulation replications.
alpha: Significance level.

Value

Estimated power (a number between 0 and 1).

References

Howard, M. C., & Melloy, R. C. (2016). Evaluating item-sort task methods: The presentation of a new statistical significance formula and methodological best practices. Journal of Business and Psychology, 31(1), 173–186. doi:10.1007/s10869-015-9404-y

Examples

simulate_csv_power(N = 20, true_p = 0.65, reps = 100, alpha = 0.05)
#> [1] 0.31