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Ability and Prior Distribution Mismatch: An Exploration of Common-Item Linking Methods.

ABSTRACT: Linking of two forms is an important task when using item response theory, particularly when two forms are administered to nonequivalent groups. When linking with characteristic curve methods, the ability distribution and weights associated with that distribution can be used to weight observations differently. These are commonly specified as equally spaced intervals from -4 to 4, but other options or distributional forms can be specified. The use of these different distributions and weights of the ability distributions will be explored with a Monte Carlo simulation. Primary simulation conditions will include sample size, number of items, number of common items, ability distribution, and randomly varying population transformation constants. Study results show that the linking weights have little impact on the estimation of the linking constants; however, the underlying ability distribution of examinees does have significant impact. Implications for applied researchers will be discussed.

SUBMITTER: LeBeau B

PROVIDER: S-EPMC5978475 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Ability and Prior Distribution Mismatch: An Exploration of Common-Item Linking Methods.

LeBeau Brandon B

Applied psychological measurement 20170518 7

Linking of two forms is an important task when using item response theory, particularly when two forms are administered to nonequivalent groups. When linking with characteristic curve methods, the ability distribution and weights associated with that distribution can be used to weight observations differently. These are commonly specified as equally spaced intervals from -4 to 4, but other options or distributional forms can be specified. The use of these different distributions and weights of t ...[more]

PMID: 29881105

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Project description:BackgroundResearch on health anxiety has bloomed in recent years, but summaries of the literature are complicated by the use of dissimilar self-report questionnaires. Furthermore, these instruments have rarely been administered in parallel, and especially not in clinical samples. In this study, we aimed to investigate the relationship between five widespread health anxiety measures, and to draft guidelines for the conversion of different sum scores.MethodsClinical trial participants with principal pathological health anxiety (n = 335) and a sample of healthy volunteers (n = 88) completed the 14-item Whiteley Index (WI-14), the Illness Attitude Scale (IAS), and the 14-, 18-, and 64-item Health Anxiety Inventory (the HAI-64, HAI-18, and HAI-14). Cross-sectional data from all participants were pooled (N = 423) and we conducted a joint factor analysis and approximate equipercentile linking of the WI-14, IAS, HAI-64, HAI-18, and HAI-14.ResultsInter-scale correlations were high (rs ≥ 0.90 and ≥ 0.88 in adjusted analyses), and the scree plot of the joint factor analysis spoke for a unifactorial solution where 89/105 items (85%) had loadings ≥ 0.40. Most items at the core of this broad trait health anxiety factor pertained to the worry about health, the fear of having or developing a serious disease, and to some extent bodily preoccupation. We present a cross-walk table of observed equipercentile linked sum scores.ConclusionsThis study speaks clearly in favor of the WI-14, IAS, HAI-64, HAI-18, and HAI-14 all tapping into the same trait health anxiety construct, the core of which appears to concern the worry about health, the fear of having or developing a serious disease, and to some extent bodily preoccupation. Based on recently reported cut-offs for the HAI-14, a reasonable cutoff for pathological health anxiety in a psychiatric setting probably lies around 7-8 on the WI-14, 52-53 on the IAS, 82-83 on the HAI-64, and 26-27 on the HAI-18.Trial registrationClinicalTrials.gov NCT01966705, NCT02314065.

Dataset Information

Ability and Prior Distribution Mismatch: An Exploration of Common-Item Linking Methods.

Publications

Ability and Prior Distribution Mismatch: An Exploration of Common-Item Linking Methods.

Similar Datasets

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