A comparison of three approaches for clustering polytomous data in the presence of masking variables

Sijia Huang; Preston Botter; Alexandra Sturm

doi:10.3389/feduc.2025.1645911

A comparison of three approaches for clustering polytomous data in the presence of masking variables

Sijia Huang
, Preston Botter
, Alexandra Sturm

Psychological Science

Indiana University School of Education

Research output: Contribution to journal › Article › peer-review

Original language	English
Article number	1645911
Journal	Frontiers in Education
Volume	10
DOIs	https://doi.org/10.3389/feduc.2025.1645911
State	Published - 2026

ASJC Scopus Subject Areas

Education

Keywords

clustering
k-means
k-medians
latent class analysis
polytomous data

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10.3389/feduc.2025.1645911

Cite this

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title = "A comparison of three approaches for clustering polytomous data in the presence of masking variables",

keywords = "clustering, k-means, k-medians, latent class analysis, polytomous data",

author = "Sijia Huang and Preston Botter and Alexandra Sturm",

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year = "2026",

doi = "10.3389/feduc.2025.1645911",

language = "English",

volume = "10",

journal = "Frontiers in Education",

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T1 - A comparison of three approaches for clustering polytomous data in the presence of masking variables

AU - Huang, Sijia

AU - Botter, Preston

AU - Sturm, Alexandra

PY - 2026

Y1 - 2026

KW - clustering

KW - k-means

KW - k-medians

KW - latent class analysis

KW - polytomous data

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DO - 10.3389/feduc.2025.1645911

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SN - 2504-284X

VL - 10

JO - Frontiers in Education

JF - Frontiers in Education

M1 - 1645911

ER -

A comparison of three approaches for clustering polytomous data in the presence of masking variables

ASJC Scopus Subject Areas

Keywords

Access to Document

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Cite this