2012
DOI: 10.2333/jbhmk.39.81
|View full text |Cite
|
Sign up to set email alerts
|

The Effect of Local Dependence on Item Parameter Estimation

Abstract: In this study, we assessed the effect of local dependence on item parameter estimation based on comparable item parameters, using Markov Chain Monte Carlo method. The results showed that if we estimate item parameters ignoring local dependence, item parameter estimation will be more inaccurate than taking local dependence into account. Furthermore, it was supposed that the result of previous works, which were not based on comparable item parameters, was distorted.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2019
2019

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…However, care should be exercised in interpreting the finding that Item 3 in the scale showed slight local dependence with the other two items, probably because of redundancy-dependency of the item contents (i.e., similar items are included in the same scale). Although the degree of overlap is not so large and should be interpreted in accordance with the number of items in the scale, this may produce overestimation of the scale parameter and underestimation of the location parameter of the item [25] and may result in overestimation of scale reliability [26]. Another point to mention is that the Item Information Curve (IIC) reveals that the item “I feel that I lack companionship” may not be effective for the discrimination of loneliness.…”
Section: Discussionmentioning
confidence: 99%
“…However, care should be exercised in interpreting the finding that Item 3 in the scale showed slight local dependence with the other two items, probably because of redundancy-dependency of the item contents (i.e., similar items are included in the same scale). Although the degree of overlap is not so large and should be interpreted in accordance with the number of items in the scale, this may produce overestimation of the scale parameter and underestimation of the location parameter of the item [25] and may result in overestimation of scale reliability [26]. Another point to mention is that the Item Information Curve (IIC) reveals that the item “I feel that I lack companionship” may not be effective for the discrimination of loneliness.…”
Section: Discussionmentioning
confidence: 99%