Computing maximum likelihood estimates of loglinear models from marginal sums with special attention to loglinear item response theory

DOI10.1007/BF02295431zbMath0850.62863OpenAlexW1987698650MaRDI QIDQ1205788

Henk Kelderman

Publication date: 1 April 1993

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02295431

Mathematics Subject Classification ID

Point estimation (62F10) Probabilistic methods, stochastic differential equations (65C99) Applications of statistics to psychology (62P15)

Related Items (6)

Latent Regression in Loglinear Rasch Models ⋮ Testing the Fit of Latent Regression Models ⋮ Loglinear multidimensional IRT models for polytomously scored items ⋮ Loglinear Rasch models for the analysis of stability and change ⋮ Fitting and testing conditional multinormal partial credit models ⋮ Item screening in graphical loglinear Rasch models

Uses Software

• LINPACK
• SPSS

Cites Work

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• Characterizing the manifest probabilities of latent trait models
• Loglinear Rasch model tests
• A note on the computation of the second-order derivatives of the elementary symmetric functions in the Rasch model
• A Rasch model for partial credit scoring
• On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known
• Testing the philosophy of mathematics in the history of mathematics

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