PLS-SEM 偏最小平方法結構方程模型

Overview

PLS-SEM (Wold, 1982; Hair et al., 2017) is a variance-based approach to structural equation modeling that estimates composite-based path models. Unlike CB-SEM, it maximizes explained variance in endogenous constructs and readily handles both reflective and formative measurement models.

When to Use

• Formative measurement models are part of the research design
• Sample size is small (PLS works with N ≥ 10× the largest number of paths pointing to any construct)
• Research goal is prediction and variance explanation rather than theory confirmation
• The structural model is complex with many constructs and indicators

When NOT to Use

• Research goal is strict theory testing and model fit assessment
• All constructs are reflective and sample size is adequate for CB-SEM
• You need global model fit indices (chi-square, CFI, RMSEA)
• Circular relationships (non-recursive models) are hypothesized