This paper challenges the prevailing practice of accepting standardized factor loadings as low as .50 in confirmatory factor analysis. Drawing on the logic of Average Variance Extracted (AVE) and communality, the author argues for a stricter item level threshold: only indicators with loadings of λ >= .70 (implying λsq >= .50) should be retained in final measurement models. The rationale is that indicators with λ < .70 contain more error than explained variance, undermining both construct validity and the stability of factor solutions. The paper reviews theoretical foundations, simulation evidence, and implications for structural equation modeling, showing that weak loadings degrade measurement quality, factor score determinacy, and model fit. Adopting a minimum λ >= .70 rule aligns item level standards with established construct level criteria and enhances the rigor and interpretability of latent variable models.

翻译：本文挑战了验证性因子分析中普遍接受的标准化因子载荷低至0.50的做法。基于平均方差提取量（AVE）和共同度逻辑，作者主张更严格的项目层面阈值：最终测量模型中应仅保留载荷λ ≥ .70（即λ² ≥ .50）的指标，其依据在于λ < .70的指标所含误差方差大于解释方差，这会损害构念效度与因子解的稳定性。本文回顾了理论基础、模拟证据及对结构方程模型的影响，表明弱载荷会降低测量质量、因子分数确定性和模型拟合度。采用λ ≥ .70最低阈值规则能使项目层面标准与既有构念层面标准保持一致，并增强潜变量模型的严谨性与可解释性。