本研究旨在比較台灣三地區高一學生在空間能力之表現差異，使用工具為標準化空間能力測驗，其空間因素為空間視覺與空間定位雙因素模式，共計18題。本研究樣本經合併後，分為三區，並經由全列刪除法，最後實際使用樣本數為1488人。
本研究主要是利用多樣本結構方程模式，先驗證標準化空間能力測驗的雙因素結構具有區域恆等性，進而比較各區的潛在因素平均數，並將比較結果與使用觀察分數的變異數分析結果相較，兩種分析方法得到相同結果。研究結果顯示，三區域的高一生在空間能力、空間視覺和空間定位均有顯著差異，其中北區和南區有顯著差異，中區和南區有顯著差異，而北區和中區則無顯著差異。
本研究建議一套完整的多樣本恆等性檢驗流程，可提供後續測驗研發者欲探討跨群組差異比較之參考，此檢驗依序為模式型貌，因素負荷量、截距、測量誤差、潛在因素變異數與潛在因素共變數等參數檢驗，六項檢驗恆等均成立後，才能檢驗潛在因素平均數結構。本研究針對使用觀察分數平均數和潛在因素平均數的差異比較進行探討，分析使用潛在因素平均數的優點，並建議後續研究。

The purpose of the study is to compare the differences of spatial ability of the 10th grade students across three areas in Taiwan. The instrument used is the standardized spatial ability test (SSAT) constructed by two spatial factors-visualization and spatial orientation, with 18 test items. After listwise deletion, the final number of sample is 1488, and is reorganized into three areas (the North, the Middle, and the South areas).
The main focus of the study is to apply the multi-groups structural equation model (Multi-groups SEM) to test if the baseline model of the two spatial factors of SSAT is measurement invariant across three areas. After parameter tests of invariances are confirmed, the latent factor means can be compared across areas. The comparison results using latent factor means are further compared with those obtained from the usual analysis of variances (ANOVA) using observed mean scores. The results of differences with Multi-groups SEM and ANOVA are basically the same, that is, there are significant differences in sptial ability, visualization, and spatial orientation across areas; the North is significantly higher than the South, the Middle is significantly higher than the South, and the North is not significantly different from the Middle.
The study suggests a complete analysis procedure for testing multi-groups invariance, including sequentially configural invariance, factor loading invariance, scalar/intercept invariance, measurement error invariance, latent factor variance invariance, and latent factor covariance invariance. After these six invariance tests of parameters are satisfied, the latent factor mean structure is tested and compared. The study provides discussions about the strengths in using Multi-groups SEM as compared with ANOVA for difference comparison, and recommends future applications and research.

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