Heywood cases in unidimensional factor models and item response models for binary data
二元数据单维因子模型与项目反应模型中的 Heywood 情形
Heywood cases are known from linear factor analysis literature as variables with communalities larger than 1.00, and in present day factor models, the problem also shows in negative residual variances. For binary data, ordinal factor models can be applied with either delta parameterization or theta parametrization. The former is more common than the latter and can yield Heywood cases when limited information estimation is used. The same problem shows up as nonconvergence…