Analysis of multivariate categorical data with misclassification errors by triple sampling schemes

DOI10.1016/0378-3758(84)90018-1zbMath0529.62008OpenAlexW1963582024MaRDI QIDQ787609

T. Timothy Chen, Aaron Tenenbein, Yosef Hochberg

Publication date: 1984

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(84)90018-1

zbMATH Keywords

maximum likelihoodtraffic safetymisclassificationfitting log- linear modelsmultivariate categorical datatriple sampling schemes

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Point estimation (62F10) Sampling theory, sample surveys (62D05) Applications of statistics (62P99)

Related Items (1)

Acceleration of the EM and ECM algorithms using the Aitken \(\delta^2\) method for log-linear models with partially classified data

Cites Work

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• On the Use of Double Sampling Schemes in Analyzing Categorical Data with Misclassification Errors
• A Double Sampling Scheme for Estimating from Misclassified Multinomial Data with Applications to Sampling Inspection
• The analysis of multidimensional contingency tables when some variables are posterior to others: a modified path analysis approach

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