A Latent Class Extension of Signal Detection Theory, with Applications
A Latent Class Extension of Signal Detection Theory, with Applications
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信号检测理论的潜在类扩展及其应用
DOI：
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发表时间：
2002
影响因子：
3.8
通讯作者：
L. T. DeCarlo
中科院分区：
文献类型：
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作者：
L. T. DeCarlo
提出了信号检测理论的一个潜在类扩展，并举例说明了其应用。该方法是有用的情况下，观察员试图检测潜在的分类事件或分析的目标是选择或分类的情况。信号检测理论提供了一个简单的总结观察员的性能方面的检测和响应标准。通过信号检测的意见，为培训的评级员的影响，是验证参数和分类的方法。信号检测模型的扩展到两个以上的潜在类，与一个简单的限制检测参数，介绍。提供了使用潜在类分析软件或第二代结构方程建模软件拟合模型的示例程序。
A latent class extension of signal detection theory is presented and applications are illustrated. The approach is useful for situations where observers attempt to detect latent categorical events or where the goal of the analysis is to select or classify cases. Signal detection theory is shown to offer a simple summary of the observers' performance in terms of detection and response criteria. Implications of the view via signal detection for the training of raters are noted, as are approaches to validating the parameters and classifications. An extension of the signal detection model to more than two latent classes, with a simple restriction on the detection parameters, is introduced. Sample programs to fit the models using software for latent class analysis or software for second generation structural equation modeling are provided.