ArticleAssessment2023
How Accurate and Consistent Are Score-Based Assessment Decisions? A Procedure Using the Linear Factor Model.
Article in Assessment, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Estimating classification consistency of machine learning models for screening measures.Psychological assessmentArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
When scales or tests are used to make decisions about individuals (e.g., to identify which adults should be assessed for psychiatric disorders), it is crucial that these decisions be accurate and consistent. However, it is not obvious how to assess accuracy and consistency when the scale was administered only once to a given sample and the true condition based on the latent variable is unknown. This article describes a method based on the linear factor model for evaluating the accuracy and consistency of scale-based decisions using data from a single administration of the scale. We illustrate the procedure and provide R code that investigators can use to apply the method in their own data. Finally, in a simulation study, we evaluate how the method performs when applied to discrete (vs. continuous) items, a practice that is common in published literature. The results suggest that the method is generally robust when applied to discrete items.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.