TY - GEN
T1 - Polychoric correlations for ordered categories using the EM algorithm
AU - Shiina, Kenpei
AU - Ueda, Takashi
AU - Kubo, Saori
N1 - Funding Information:
Acknowledgements This work was supported by JSPS KAKENHI Grant Numbers 23530871 and 16H02050. Correspondence concerning this article should be addressed to Kenpei Shiina, Department of Educational Psychology, School of Education, Waseda University, Shinjuku-ku, Tokyo, 169-8050, JAPAN.
Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - A new method for the estimation of polychoric correlations is proposed in this paper, which uses the Expectation-Maximization (EM) algorithm and the Conditional Covariance Formula. Simulation results show that this method attains the same level of accuracy as other methods, and is robust to deteriorated data quality.
AB - A new method for the estimation of polychoric correlations is proposed in this paper, which uses the Expectation-Maximization (EM) algorithm and the Conditional Covariance Formula. Simulation results show that this method attains the same level of accuracy as other methods, and is robust to deteriorated data quality.
KW - Conditional covariance formula
KW - EM algorithm
KW - Polychoric correlation
UR - http://www.scopus.com/inward/record.url?scp=85045980876&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045980876&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-77249-3_21
DO - 10.1007/978-3-319-77249-3_21
M3 - Conference contribution
AN - SCOPUS:85045980876
SN - 9783319772486
T3 - Springer Proceedings in Mathematics and Statistics
SP - 247
EP - 259
BT - Quantitative Psychology - The 82nd Annual Meeting of the Psychometric Society, Zurich, Switzerland, 2017
A2 - Gonzalez, Jorge
A2 - Janssen, Rianne
A2 - Wiberg, Marie
A2 - Molenaar, Dylan
A2 - Culpepper, Steven
PB - Springer New York LLC
T2 - 82nd Annual meeting of the Psychometric Society, 2017
Y2 - 17 July 2017 through 21 July 2017
ER -