# XXC@Note

##### Differences

This shows you the differences between two versions of the page.

 — structural_equation_modeling [2016/10/23 04:12] (current) Line 1: Line 1: + == Structural Equation Modeling [SEM, 結構方程模式]== + + **結構方程模式(Structural Equation Modeling, SEM)**是一種結合了質性因果假設與統計資料，進行測試與估計因果關係的統計方法。 + + **結構方程模式**能發展理論與測試理論，即能有探索模式(exploratory)與檢驗模式(confirmatory)。 + 檢驗模式通常來自於一個因果模型的假設，此因果假設的概念必須被操作化才能在模式中，以實際測量到的資料檢驗，是否符合假設模型的因果關係。 + + 結構方程模式也能根據給定模型，就現有資料歸納出理論模型間的參數評估值。通常，初期假設模型需要透過證據作修改。當**結構方程模式**用於純粹的探索研究時，通常在探索心理評量因素分析的脈絡下。 \\ (With an initial theory SEM can be used inductively by specifying a corresponding model and using data to estimate the values of free parameters. Often the initial hypothesis requires adjustment in light of model evidence. When SEM is used purely for exploration,​ this is usually in the context of exploratory factor analysis as in psychometric design.) + + **結構方程模式**的優勢在於其建構潛在變數的能力：這些變數無法被直接的量測，但在模型中，可透過一些可測量變數被作為可預測的潛在變處來評估。這能讓模型建構者能明確的捕捉模型中不可靠的測量值，。因素分析、路徑分析與 ​ + + This allows the modeler to explicitly capture the unreliability of measurement in the model, which in theory allows the structural relations between latent variables to be accurately estimated. Factor analysis, path analysis and regression all represent special cases of SEM. + + + + [Translate from [[wp>​Structural Equation Modeling]](2011-Apr-12)] + + + == Content == + + == Note == + + == Metadata/​Backlinks == + + {{backlinks>​.}} + {{tag>​Statics}}