Statistical methods for a general theory of all-or-none learning
- 1 March 1970
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 35 (1) , 51-72
- https://doi.org/10.1007/bf02290593
Abstract
Greeno and Steiner have shown that a three state Markov Chain with a single absorbing state is equivalent to many of the current formalizations of All-or-None learning theories. Distribution statistics and other summary statistics are derived from the general model. Expressions for the maximum likelihood estimators of its parameters and the sampling variances of the estimates are presented. Likelihood ratio tests for several different null hypotheses are derived. These tests permit one to evaluate the usual null hypotheses in terms of the parameters of a process model.Keywords
This publication has 14 references indexed in Scilit:
- Comments on “Markovian Processes with Identifiable States: General Considerations and Applications to All-or-None Learning”Psychometrika, 1968
- Paired-associate learning with short-term retention: Mathematical analysis and data regarding identification of parametersJournal of Mathematical Psychology, 1967
- All-or-none transfer based on verbally mediated conceptsJournal of Mathematical Psychology, 1966
- A forgetting model for paired-associate learningJournal of Mathematical Psychology, 1965
- Markovian Processes with Identifiable States: General Considerations and Application to All-or-None LearningPsychometrika, 1964
- A comparison of paired-associate learning models having different acquisition and retention axiomsJournal of Mathematical Psychology, 1964
- An association model for response and training variables in paired-associate learning.Psychological Review, 1962
- Statistical Methods for a Theory of Cue LearningPsychometrika, 1961
- Application of a Model to Paired-Associate LearningPsychometrika, 1961
- Learning theory and the new "mental chemistry."Psychological Review, 1960