Assessing Fit and Dimensionality in Least Squares Metric Multidimensional Scaling Using Akaike’s Information Criterion

Cody S. Ding; Mark L. Davison

doi:10.1177/0013164409344554

Assessing Fit and Dimensionality in Least Squares Metric Multidimensional Scaling Using Akaike’s Information Criterion

University of Missouri-St. Louis

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

Original language	American English
Journal	Educational and Psychological Measurement
Volume	70
DOIs	https://doi.org/10.1177/0013164409344554
State	Published - Jan 4 2010

Disciplines

Econometrics
Mathematics
Statistics and Probability

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10.1177/0013164409344554License: Unspecified

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title = "Assessing Fit and Dimensionality in Least Squares Metric Multidimensional Scaling Using Akaike{\textquoteright}s Information Criterion",

author = "Ding, {Cody S.} and Davison, {Mark L.}",

note = "Akaike's information criterion is suggested as a tool for evaluating fit and dimensionality in metric multidimensional scaling that uses least squares methods of estimation. This criterion combines the least squares loss function with the number of estimated parameters. Numerical examples are presented.",

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doi = "10.1177/0013164409344554",

language = "American English",

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T1 - Assessing Fit and Dimensionality in Least Squares Metric Multidimensional Scaling Using Akaike’s Information Criterion

AU - Ding, Cody S.

AU - Davison, Mark L.

N1 - Akaike's information criterion is suggested as a tool for evaluating fit and dimensionality in metric multidimensional scaling that uses least squares methods of estimation. This criterion combines the least squares loss function with the number of estimated parameters. Numerical examples are presented.

PY - 2010/1/4

Y1 - 2010/1/4

UR - https://experts.umn.edu/en/publications/assessing-fit-and-dimensionality-in-least-squares-metric-multidim

U2 - 10.1177/0013164409344554

DO - 10.1177/0013164409344554

M3 - Article

VL - 70

JO - Educational and Psychological Measurement

JF - Educational and Psychological Measurement

ER -

Assessing Fit and Dimensionality in Least Squares Metric Multidimensional Scaling Using Akaike’s Information Criterion

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