partgam_LD: Partial Gamma to detect Local Dependence (LD)

In iarm: Item Analysis in Rasch Models

Partial Gamma to detect Local Dependence (LD)

Description

Rasch models assume locally independent items. There should be no substantial correlation left between two items once the underlying factor has been taken into account. Partial Gamma coefficients between pairs of items controlled for the rest score can be used to assess this requirement. The rest score is calculated as the score without the second item.

Usage

partgam_LD(
  dat.items,
  p.adj = c("BH", "holm", "hochberg", "hommel", "bonferroni", "BY", "none")
)

Arguments

dat.items	A data frame with the responses to the items.
p.adj	Correction method for multiple testing. The methods are "BH","holm", "hochberg", "hommel", "bonferroni", "BY", "none". See p.adjust.

Details

Because it matters which of the two items of a pair is subtracted from the total score to give the rest score, calculations are done for each pair in both ways. Results are stored in two different data frames.

Value

list of two data frames with Gamma coefficients, standard errors, p values, adjusted p values if an adjustment method has be chosen, and confidence limits for every pair of items.

Author(s)

Marianne Mueller

References

Christensen, K. B. , Kreiner, S. & Mesbah, M. (Eds.) Rasch Models in Health. Iste and Wiley (2013), pp. 133 - 135.

See Also

partgam_DIF

Examples

partgam_LD(amts[,4:13])

iarm documentation built on Aug. 27, 2022, 5:06 p.m.