本研究透過驗證性因素分析與模式競爭，為標準化空間能力測驗找尋最佳與最簡約的模式，因為根據該測驗的編製發展歷程，共有七個可能的模式，包含了一階層、二階層、及三階層的模式。
本研究資料為標準化空間能力測驗的常模資料，樣本為台灣地區高一學生1,641人；該測驗共計18題，分屬四個題型與兩個空間因素，測驗資料屬對或錯的二元計分變項。
本研究同時採用最大概似估計法和對角線加權最小平方法進行參數估計，以比較不同參數估計方法對於分析結果的影響。結果發現，通過對角線加權最小平方法估計的模式較最大概似估計法為多，亦即適配的模式較多。在對角線加權最小平方法估計下，有六個模式能達到良好的適配，而在最佳模式的競爭上，兩種估計法皆選擇一個二階層模式架構，包含一階潛在變項為四個題型，第二階潛在變項為空間能力。
研究結果確認本測驗具高階層驗證模式架構，除最簡約的二階層模式外，其它的高階層結構模式不盡然比低階層更為簡約，唯研究結果可能受限於本測驗在因素、題型與試題數量上的限制。未來在本測驗的應用與解釋上，本研究結果的二階層模式能有最好的解釋。未來若有機會修訂測驗時，若能適度擴增因素、題型與試題數量組合的話，將有助於高階層結構的穩定性。

The purpose of the study is to find the best and the most parsimonius explanatory model for the standardized spatial ability test (SPAT) through higher-order confirmatory factor analysis and model competition, because based on SPAT’s development and construction algorithm, there are seven possible structure models underlie SPAT, including first-, second-, and third-order models.
The data used is SPAT’s norm sample, which are 1,641 first-year senior high school students. There are 18 test items categorized into four item types and two spatial factors.
In parameter estimation, maximum likelihood estimation (ML) and diagonally weighted least squares (DWLS) are both applied to compare their differential impact. Results show that the number of models fitted well by DWLS is more than those by ML. The choice of the best and parsimonious model by both estimation methods is the same second-order structure of which, the first order being the four item types, and the second order being the test construct - spatial ability.
It is confirmed that SPAT is of higher-order structure. But besides the choice of the second-order structure, other higher-order structure models are not better than lower-order ones. The reason may be that there is limited number of spatial factors in SPAT, there is limited number of item types in the factors, and there is limited number of items in the item types. The choice of the second-order structure can be used in SPAT’s future application and explanation. If future edition and reconstruction is possible, it would be appropriate that the numbers of factors, item types, and items be increased to stabilize SPAT’s higher-order measurement structure.

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