This paper compares the predictive powers of hierarchical generalized linear modeling (HGLM), logistic regression, and discriminant analysis with regard to tenure choices between buying property and renting property by sampling the residents of the Greater Taipei area. The results imply that the hit rate and other indicators included in HGLM have better predictive power with regard to tenure choices than the binary logistic regression model and the discriminant analysis model. That is, using HGLM to process nested data can increase prediction accuracy regarding household tenure choices. Furthermore, cross-validation is performed to analyze hit rate stability. The hit rate sequencing from this cross-validation is found to be consistent with the HGLM results, implying that the comparison of the three models in terms of hit rate performance prediction in this study is stable and reliable.

中文翻译：

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财产所有权与租赁权能选择权预测能力的比较

本文通过对大台北地区的居民进行抽样，比较了分层广义线性建模（HGLM），逻辑回归和判别分析在购买物业和租赁物业之间的任期选择方面的预测能力。结果表明，与二元逻辑回归模型和判别分析模型相比，HGLM包含的命中率和其他指标对任期选择具有更好的预测能力。也就是说，使用HGLM处理嵌套数据可以提高有关家庭使用权选择的预测准确性。此外，执行交叉验证以分析命中率稳定性。发现此交叉验证的命中率排序与HGLM结果一致，