5 綜合討論
5.3 知感的個別差異
在目前的機率模型分析裡面，個別差異是沒有被考量的，一方面是礙於統合 分析的限制，我所使用的都是經過帄均的資料，另一方面是以最大概似法估計出 來的參數都是一個定值，即使這個值可以很好地適配帄均過後的資料，也不能推
論它可以大致適合於每一個個體(Klauer, 2006)。但是知感的個別差異一定是相當 大的，我認為未來解決的辦法是必須要嘗詴貝氏統計(Bayesian statistics)的估計，
Smith & Batchelder (2010)提出採用貝氏統計來分析多項歷程樹狀模型的 Beta- MPT 模型，這種模型的基本改變是將隨機效果(random effect)加入，參數估計不 再為一定值，而是呈現一個分配，加上貝氏的推論統計，可以回答個別受詴者的 參數在這個分配裡有多高的機率出現。雖然這樣的技術現階段還不是非常成熟，
但是我認為使用分配的概念，這樣的參數估計才有可能更好地捕捉知感個別差異 的豐富性，協助心理學家更貼近知感精確度的真正內涵。
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