Latent structureScale / measurement
多分类构念效度
多分类构念效度（Polytomous Construct Validity）是指评估由有序、多类别项目（例如，李克特量表或评定量表项目）组成的量表是否真实地测量了预期的潜在构念。它将经典的效度框架扩展到多分类测量模型——例如等级反应模型（Graded Response Model）或广义部分得分模型（Generalized Partial Credit Model）——以确保有序反应类别按设计运行，并且由此产生的得分反映了目标构念。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176. DOI: 10.1177/014662169201600206 ↗
- Embretson, S. E., & Reise, S. P. (2000). Item Response Theory for Psychologists. Lawrence Erlbaum Associates. ISBN: 978-0805828191
如何引用本页
ScholarGate. (2026, June 3). Polytomous Construct Validity Assessment. ScholarGate. https://scholargate.app/zh/psychometrics/polytomous-construct-validity
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 验证性因子分析（CFA）心理测量学↔ compare
- 差异项目功能 (DIF)心理测量学↔ compare
- 探索性因子分析（EFA）统计学↔ compare
- 分级反应模型 (GRM)心理测量学↔ compare
- 部分信用模型 (PCM / GPCM)心理测量学↔ compare
- 多分类Rasch模型心理测量学↔ compare