ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

多项式项目分析×验证性因子分析(CFA)×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份1969–19821969
提出者Fumiko Samejima (graded response model, 1969); David Andrich (rating scale model, 1978); Geoffrey Masters (partial credit model, 1982)Karl Gustav Jöreskog
类型Item-level psychometric analysisHypothesis-testing latent variable model
开创性文献Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, 34(4, Pt. 2), 1–97. DOI ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
别名ordered-category item analysis, graded response analysis, polytomous IRT, rated-scale item analysisCFA, confirmatory FA, measurement model, restricted factor analysis
相关44
摘要Polytomous item analysis examines the psychometric behavior of items that have more than two ordered response categories — such as Likert-type scales or partial-credit tasks. It evaluates each item's difficulty thresholds, discriminating power, and category functioning to determine whether the full response scale is being used as intended and whether each item contributes reliably to measuring the underlying construct.Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Polytomous item analysis · Confirmatory factor analysis. 于 2026-06-18 检索自 https://scholargate.app/zh/compare