How to fit models of recognition memory data using maximum likelihood

被引：0

作者：

Dunn, John C. ^{[1
]}

机构：

[1] Univ Adelaide, Adelaide, SA, Australia

来源：

INTERNATIONAL JOURNAL OF PSYCHOLOGICAL RESEARCH | 2010年 / 3卷 / 01期

基金：

澳大利亚研究理事会;

关键词：

Recognition memory; maximum likelihood estimation; signal detection theory; mixture models; high threshold models;

D O I：

暂无

中图分类号：

B84 [心理学];

学科分类号：

04 ; 0402 ;

摘要：

The aim of this paper is to provide an introductory tutorial to how to fit different models of recognition memory using maximum likelihood estimation. It is in four main parts. The first part describes how recognition memory data is collected and analysed. The second part introduces four current models that will be fitted to the data. The third part describes in detail how a model is fit using maximum likelihood estimation. The fourth part examines how the fit of a model can be evaluated and the appropriate statistical test applied.

引用

页码：140 / 149

页数：10

共 9 条

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