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+++ title = "Visualizing different levels of compensation in multidimensional item response theory models" date = 2017-12-01T00:00:00 draft = false

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authors = ["W. Jake Thompson"]

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2 = Journal article

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publication_types = ["2"]

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publication = "Educational Measurement: Issues and Practice" publication_short = "EM:IP"

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abstract = "This graphic shows the probability of providing a correct response to an item in a multidimensional item response theory (MIRT) model. The colors represent the probability of a correct response, and the contours represent chunk of 10% probability (i.e., the space between the leftmost and second contours represents ability pairs with a 10-20% probability of answering correctly). These plots show how the 1PL, 2PL, and 3PL MIRT models are affected by how compensatory the model is parameterized to be. Additionally, creating 2-dimensional representations of the 3-dimensional curves makes it easier to identify differences in between the partially compensatory and noncompensatory models that tend to look very similar when rendered in 3 dimensions."

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selected = true

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content/project/deep-learning/index.md.

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projects = []

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tags = ["educational-assessment", "rstats", "ggplot2", "tidyverse"]

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url_pdf = "pub/2017-emip-cover-article.pdf" url_preprint = "" url_code = "" url_dataset = "" url_project = "" url_slides = "" url_video = "" url_poster = "" url_source = ""

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url_custom = [{name = "Cover", url = "pub/2017-emip-cover.pdf"}, {name = "Code", url = "https://gist.github.com/wjakethompson/084c0b9ddbea5c8a45078b0eba6629ec"}]

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doi = "10.1111/emip.12177"

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math = true

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[image]

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caption = ""

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focal_point = "" +++