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結構方程模式(SEM)
Structure Equation Modeling
此方法最早由基因學家Sewall Wright(1921)提出,經濟學家Trygve Haavelmo(1943)與認知科學家Herbert A. Smith(1953)亦有相關之研究,最後由美國電腦暨統計學家Judea Pearl(2000)定名為SEM。SEM主要由兩部分組成,測量模式(measurement model)與結構模式(structure model)。在測量模式中使用驗證性因素分析(Confirmatory Factor Analysis, CFA)建構觀察變數與”潛在變數(latent variable)”間的關係;在結構模式中則利用徑向分析(Path Analysis)來探討變數間的因果關係,以建立模式架構。SEM已大量應用於社會科學、行為科學等領域,及市場調查研究領域上等,成為主流的研究方法之一。

本方法使用之R相關套件與參考文獻:
相關套件:stats、base、lavaan、stringr、semPlot、semTools、mvnormtest
參考文獻:(依套件名稱排序)
  1. R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL:http://www.R-project.org/.
  2. Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL:http://www.jstatsoft.org/v48/i02/.
  3. Hadley Wickham (2012). stringr: Make it easier to work with strings.. R package version 0.6.2. URL:http://CRAN.R-project.org/package=stringr
  4. Sacha Epskamp (2013). semPlot: Path diagrams and visual analysis of various SEM packages' output. R package version 0.3.3. URL:http://CRAN.R-project.org/package=semPlot
  5. Sunthud Pornprasertmanit, Patrick Miller, Alexander Schoemann and Yves Rosseel (2013). semTools: Useful tools for structural equation modeling.. R package version 0.4-0. URL:http://CRAN.R-project.org/package=semTools
  6. Slawomir Jarek (2012). mvnormtest: Normality test for multivariate variables. R package version 0.1-9. URL:http://CRAN.R-project.org/package=mvnormtest
範例F-5:

數學家高斯曾說過”數學為科學之母”,數學的希臘語辭源為”學問的基礎”(取自維基百科),由此可見數學的重要性。某中學老師欲了解學生的數學能力,以Holzinger & Swineford (1939)之問卷對該校七、八年級學生進行智力測驗分析。問卷含五種構念I (空間、語言、速度、記憶及數學能力)並以24道試題呈現。隨機抽取145名七、八年級學生為施測對象協助完成測驗。資料包含性別、年齡(年)、年齡(月)、24道試題成績與年級,記錄如下表,資料說明於表後。

表:智力測驗分析表
編號 性別 年齡(年) 年齡(月) t1 t2 t3 t4 t5 ... t23 t24 年級
1 1 13 0 23 19 13 4 46 ... 11 17 7
2 2 11 10 33 22 12 17 43 ... 31 32 7
3 1 12 6 34 24 14 22 36 ... 21 18 7
145 1 13 5 26 24 16 27 51 ... 31 29 8
性別:男性(1)、女性(2)
年級:七年級(7)、八年級(8)
註I:題1-4衡量空間概念、題5-9衡量語言、題10-13衡量速度、題14-19衡量記憶、題20-24衡量數學能力

Q2:在以往文獻中的研究認為影響數學能力的因素包含空間概念、語言、速度及記憶等四種能力,他們的關係為何,該如何建構分析模式?
問題解析:資料中空間概念、語言、速度及記憶等四項因素並無法直接觀測,為潛在(latent)變數,須利用問卷中的試題予以量測,並使用因素分析(Factor Analysis) 類型的統計方法。欲探討四種能力對於數學能力的影響,適合迴歸分析類型的統計方法。
統計方法:綜合問題解析中的說明,所使用的統計方法須包含具有量測能力的因素分析及能討論變數間因果關係的迴歸分析等方法。可採用分析方法:結構方程模式(SEM)。
結構方程模式 - 分析結果
  • 分析方法:結構方程模式
  • 資料名稱:範例F-5
  • 觀察變數名稱:ID, gender, ageyr, agemo, t1, t2, t3, t4, t5, t6, t7, t8, t9, t10, t11, t12, t13, t14, t15, t16, t17, t18, t19, t20, t21, t22, t23, t24, grade
  • 計算時間:5.568秒

  • 樣本敘述統計量I
    觀察變數訊息(連續變數)
    變數名稱
    Variable
    樣本數
    Count
    平均數
    Mean
    中位數
    Median
    最小值
    Minimum
    最大值
    Maximum
    標準差
    Std. dev.
    ID1457373114542.002
    gender1451.50342120.5017
    ageyr14512.72411311160.9681
    agemo1455.344850113.4809
    t114529.57933011516.9138
    t214524.8259374.445
    t314514.3034146232.8218
    t414515.9655153368.317
    t514544.848344168411.6579
    t61459.951791193.3754
    t714518.8483194284.6493
    t814528.22810435.3575
    t914517.2828162417.9475
    t1014590.1793893014923.7822
    t1114568.5931671911816.6635
    t12145109.76551106120020.995
    t13145191.779319111233337.0354
    t14145176.275917713019810.8285
    t1514589.372489731127.5424
    t16145103.4103871196.8011
    t171457.206970264.5688
    t181459.475991204.4738
    t1914515.2414164203.5964
    t2014530.344830-188719.7802
    t2114514.4552152244.8319
    t2214527.731277509.8243
    t2314518.7517191409.3605
    t2414525.82762611354.7131
    grade1457.45527780.4997

  • 觀察變數共變異數矩陣:
    IDgenderageyragemot1t2t3t4t5t6t7t8t9t10t11t12t13t14t15t16t17t18t19t20t21t22t23t24grade
    ID1764.1667-1.861124.9653-7.465314.60426.611117.944430.9167112.069411.979219.041737.729216.6458273.645895.4375165.8611350.618143.048624.986126.62521.79868.88899.812542.159724.39589.0625-18.569414.993118.1042
    gender-1.86110.2517-0.08930.0752-0.134-0.0514-0.3483-0.5728-0.22860.32310.2297-0.00420.37050.81191.4285-1.12420.42440.2560.12370.13750.42290.13380.3012-1.022-0.2585-0.197-0.06160.2818-0.0224
    ageyr24.9653-0.08930.9373-0.8834-0.228-0.08330.3273-0.01651.2148-0.1592-0.438-0.3889-0.58124.11232.35235.6644.86931.18081.44370.10420.03660.3058-0.2802-1.45980.0431-0.665-1.5065-0.35340.3
    agemo-7.46530.0752-0.883412.11642.47250.4306-1.2929-0.6477-1.7459-1.136-0.2459-0.2153-0.79263.0975-6.52540.21340.1252-4.2-0.421-1.8611-1.35660.89030.45793.9567-0.1928-0.55242.66952.1432-0.033
    t114.6042-0.134-0.2282.472547.80110.01257.260525.797926.4087.97269.935712.077817.425317.131535.251244.6507124.65659.707111.616119.71815.337611.49326.643949.243312.380328.101330.32548.90610.5192
    t26.6111-0.0514-0.08330.430610.012519.75832.387515.416714.25423.42083.29583.71396.87647.015311.17515.67540.80283.93754.51948.74030.22225.15141.763925.88196.306910.237514.19314.31250.3208
    t317.9444-0.34830.3273-1.29297.26052.38757.96288.586910.15752.483.48395.04315.83728.618811.645211.724440.65087.63793.95575.89171.64513.31991.572111.76274.52764.44337.65231.58740.2706
    t430.9167-0.5728-0.0165-0.647725.797915.41678.586969.172436.89759.206711.09216.916722.954314.763225.124841.6585114.763214.523512.87416.33335.27812.98875.390354.803616.557531.421233.32479.09820.5852
    t5112.0694-0.22861.2148-1.745926.40814.254210.157536.8975135.907424.464835.442135.843166.737687.103866.528151.4503148.264932.993519.265214.012511.330213.69088.203592.233217.979350.924247.357922.83482.1251
    t611.97920.3231-0.1592-1.1367.97263.42082.489.206724.464811.393511.27739.412519.166516.765720.22337.356739.308710.46486.33756.61674.25312.50923.046528.91954.29312.910513.66156.88750.2791
    t719.04170.2297-0.438-0.24599.93573.29583.483911.09235.442111.277321.615715.759725.32128.069119.208719.311461.230211.73665.51526.34585.32333.82274.036942.16387.062618.292217.75379.64030.5834
    t837.7292-0.0042-0.3889-0.215312.07783.71395.043116.916735.84319.412515.759728.702822.852837.783326.213932.658380.370814.07646.862510.88476.6256.07085.034745.59729.338919.116724.77929.81250.6375
    t916.64580.3705-0.5812-0.792617.42536.87645.837222.954366.737619.166525.32122.852863.162533.768438.025620.212679.993421.504812.782912.754210.35087.84377.903570.978210.446838.389136.883215.64630.5371
    t10273.64580.81194.11233.097517.13157.01538.618814.763287.103816.765728.069137.783333.7684565.5926185.2957293.1257368.435740.422426.90522.156932.740433.136317.01276.15346.174836.187556.829559.33674.7859
    t1195.43751.42852.3523-6.525435.251211.17511.645225.124866.528120.223319.208726.213938.0256185.2957277.6736147.64325.312458.446429.965135.622227.188924.68817.362867.064931.915751.896739.141332.29051.6101
    t12165.8611-1.12425.6640.213444.650715.67511.724441.658551.45037.356719.311432.658320.2126293.1257147.64440.7919410.822929.641525.886518.309726.673932.1618.1195104.595336.197741.853269.434440.93852.9061
    t13350.61810.42444.86930.1252124.656540.802840.6508114.7632148.264939.308761.230280.370879.9934368.4357325.3124410.82291371.617677.582138.568969.783332.254353.633533.6023181.375277.1081105.5652132.965762.30895.3303
    t1443.04860.2561.1808-4.29.70713.93757.637914.523532.993510.464811.736614.076421.504840.422458.446429.641577.5821117.256731.597928.104218.40789.098.516366.18899.540226.53325.423115.02710.9777
    t1524.98610.12371.4437-0.42111.61614.51943.955712.87419.26526.33755.51526.862512.782926.90529.965125.886538.568931.597956.888116.065311.936310.34244.97239.25268.461318.191117.81535.71740.5446
    t1626.6250.13750.1042-1.861119.71818.74035.891716.333314.01256.61676.345810.884712.754222.156935.622218.309769.783328.104216.065346.255610.548610.78756.208352.993111.636119.455622.58618.65970.8028
    t1721.79860.42290.0366-1.35665.33760.22221.64515.27811.33024.25315.32336.62510.350832.740427.188926.673932.254318.407811.936310.548620.87369.09535.380325.17124.169113.278312.82957.38310.4468
    t188.88890.13380.30580.890311.49325.15143.319912.988713.69082.50923.82276.07087.843733.136324.68832.16153.63359.0910.342410.78759.095320.0155.787126.82787.6514.594211.02878.56870.518
    t199.81250.3012-0.28020.45796.64391.76391.57215.39038.20353.04654.03695.03477.903517.01217.36288.119533.60238.51634.9726.20835.38035.787112.934412.10375.757412.252910.03956.33360.2713
    t2042.1597-1.022-1.45983.956749.243325.881911.762754.803692.233228.919542.163845.597270.978276.15367.0649104.5953181.375266.188939.252652.993125.171226.827812.1037391.255338.855892.683795.384834.40711.3072
    t2124.3958-0.25850.0431-0.192812.38036.30694.527616.557517.97934.2937.06269.338910.446846.174831.915736.197777.10819.54028.461311.63614.16917.655.757438.855823.346917.755220.231810.2040.6247
    t229.0625-0.197-0.665-0.552428.101310.23754.443331.421250.924212.910518.292219.116738.389136.187551.896741.8532105.565226.53318.191119.455613.278314.594212.252992.683717.755296.517446.703617.4950.6094
    t23-18.5694-0.0616-1.50652.669530.325414.19317.652333.324747.357913.661517.753724.779236.883256.829539.141369.4344132.965725.423117.815322.586112.829511.028710.039595.384820.231846.703687.618519.01940.2943
    t2414.99310.2818-0.35342.14328.90614.31251.58749.098222.83486.88759.64039.812515.646359.336732.290540.938562.308915.02715.71748.65977.38318.56876.333634.407110.20417.49519.019422.21310.5929
    grade18.1042-0.02240.3-0.0330.51920.32080.27060.58522.12510.27910.58340.63750.53714.78591.61012.90615.33030.97770.54460.80280.44680.5180.27131.30720.62470.60940.29430.59290.2497

  • 觀察變數相關係數矩陣:
    IDgenderageyragemot1t2t3t4t5t6t7t8t9t10t11t12t13t14t15t16t17t18t19t20t21t22t23t24grade
    ID1-0.08830.614-0.05110.05030.03540.15140.08850.22890.08450.09750.16770.04990.27390.13640.18810.22540.09460.07890.09320.11360.04730.0650.05070.12020.022-0.04720.07570.8626
    gender-0.08831-0.18390.0431-0.0386-0.023-0.246-0.1373-0.03910.19080.0985-0.00160.09290.0680.1709-0.10670.02280.04710.03270.04030.18450.05960.1669-0.103-0.1066-0.04-0.01310.1192-0.0894
    ageyr0.614-0.18391-0.2621-0.0341-0.01940.1198-0.00210.1076-0.0487-0.0973-0.075-0.07550.17860.14580.27870.13580.11260.19770.01580.00830.0706-0.0805-0.07620.0092-0.0699-0.1662-0.07750.6202
    agemo-0.05110.0431-0.262110.10270.0278-0.1316-0.0224-0.043-0.0967-0.0152-0.0115-0.02870.0374-0.11250.00290.001-0.1114-0.016-0.0786-0.08530.05720.03660.0575-0.0115-0.01620.08190.1306-0.019
    t10.0503-0.0386-0.03410.102710.32580.37210.44860.32760.34160.30910.32610.31710.10420.3060.30760.48680.12970.22280.41930.1690.37160.26720.36010.37060.41370.46860.27330.1503
    t20.0354-0.023-0.01940.02780.325810.19030.4170.27510.2280.15950.1560.19470.06640.15090.1680.24790.08180.13480.28910.01090.2590.11030.29440.29360.23440.34110.20580.1444
    t30.1514-0.2460.1198-0.13160.37210.190310.36590.30880.26040.26550.33360.26030.12840.24770.19790.3890.250.18590.3070.12760.2630.15490.21070.33210.16030.28970.11940.1919
    t40.0885-0.1373-0.0021-0.02240.44860.4170.365910.38050.32790.28690.37970.34730.07460.18130.23860.37260.16130.20520.28880.13890.34910.18020.33310.4120.38460.42810.23210.1408
    t50.2289-0.03910.1076-0.0430.32760.27510.30880.380510.62170.65390.57390.72030.31420.34250.21020.34340.26140.21910.17670.21270.26250.19570.40.31920.44460.4340.41560.3648
    t60.08450.1908-0.0487-0.09670.34160.2280.26040.32790.621710.71860.52050.71450.20890.35950.10380.31440.28630.24890.28820.27580.16620.2510.43310.26320.38930.43240.43290.1654
    t70.09750.0985-0.0973-0.01520.30910.15950.26550.28690.65390.718610.63270.68530.25390.24790.19780.35560.23310.15730.20070.25060.18380.24140.45850.31440.40050.4080.43990.2511
    t80.1677-0.0016-0.075-0.01150.32610.1560.33360.37970.57390.52050.632710.53670.29650.29360.29030.40510.24260.16980.29870.27070.25330.26130.43030.36080.36320.49410.38860.2381
    t90.04990.0929-0.0755-0.02870.31710.19470.26030.34730.72030.71450.68530.536710.17870.28710.12110.27180.24990.21320.2360.28510.22060.27650.45150.2720.49170.49580.41770.1352
    t100.27390.0680.17860.03740.10420.06640.12840.07460.31420.20890.25390.29650.178710.46760.58710.41830.1570.150.1370.30130.31140.19890.16190.40180.15490.25530.52940.4027
    t110.13640.17090.1458-0.11250.3060.15090.24770.18130.34250.35950.24790.29360.28710.467610.4220.52710.32390.23840.31430.35710.33120.28970.20350.39640.3170.25090.41120.1934
    t120.1881-0.10670.27870.00290.30760.1680.19790.23860.21020.10380.19780.29030.12110.58710.42210.52830.13040.16350.12820.27810.34240.10750.25190.35680.20290.35330.41370.277
    t130.22540.02280.13580.0010.48680.24790.3890.37260.34340.31440.35560.40510.27180.41830.52710.528310.19350.13810.2770.19060.32370.25230.24760.43090.29010.38360.3570.288
    t140.09460.04710.1126-0.11140.12970.08180.250.16130.26140.28630.23310.24260.24990.1570.32390.13040.193510.38690.38160.37210.18760.21870.3090.18230.24940.25080.29440.1807
    t150.07890.03270.1977-0.0160.22280.13480.18590.20520.21910.24890.15730.16980.21320.150.23840.16350.13810.386910.31320.34640.30650.18330.26310.23220.24550.25230.16080.1445
    t160.09320.04030.0158-0.07860.41930.28910.3070.28880.17670.28820.20070.29870.2360.1370.31430.12820.2770.38160.313210.33950.35450.25380.39390.35410.29120.35480.27020.2362
    t170.11360.18450.0083-0.08530.1690.01090.12760.13890.21270.27580.25060.27070.28510.30130.35710.27810.19060.37210.34640.339510.4450.32740.27850.18890.29580.30.34290.1957
    t180.04730.05960.07060.05720.37160.2590.2630.34910.26250.16620.18380.25330.22060.31140.33120.34240.32370.18760.30650.35450.44510.35970.30320.35390.3320.26340.40640.2317
    t190.0650.1669-0.08050.03660.26720.11030.15490.18020.19570.2510.24140.26130.27650.19890.28970.10750.25230.21870.18330.25380.32740.359710.17010.33130.34680.29820.37370.151
    t200.0507-0.103-0.07620.05750.36010.29440.21070.33310.40.43310.45850.43030.45150.16190.20350.25190.24760.3090.26310.39390.27850.30320.170110.40650.47690.51520.36910.1323
    t210.1202-0.10660.0092-0.01150.37060.29360.33210.4120.31920.26320.31440.36080.2720.40180.39640.35680.43090.18230.23220.35410.18890.35390.33130.406510.3740.44730.44810.2587
    t220.022-0.04-0.0699-0.01620.41370.23440.16030.38460.44460.38930.40050.36320.49170.15490.3170.20290.29010.24940.24550.29120.29580.3320.34680.47690.37410.50790.37780.1241
    t23-0.0472-0.0131-0.16620.08190.46860.34110.28970.42810.4340.43240.4080.49410.49580.25530.25090.35330.38360.25080.25230.35480.30.26340.29820.51520.44730.507910.43110.0629
    t240.07570.1192-0.07750.13060.27330.20580.11940.23210.41560.43290.43990.38860.41770.52940.41120.41370.3570.29440.16080.27020.34290.40640.37370.36910.44810.37780.431110.2517
    grade0.8626-0.08940.6202-0.0190.15030.14440.19190.14080.36480.16540.25110.23810.13520.40270.19340.2770.2880.18070.14450.23620.19570.23170.1510.13230.25870.12410.06290.25171

  • 模式訊息:
    • 模式方程式
      spatial =~ t1 + t2 + t3 + t4
      verbal =~ t5 + t6 + t7 + t8 + t9
      speed =~ t10 + t11 + t12 + t13
      memory =~ t14 + t15 + t16 + t17 + t18 + t19
      math_ability =~ t20 + t21 + t22 + t23 + t24
      math_ability ~ spatial + verbal + speed + memory
      spatial ~~ verbal
      spatial ~~ speed
      spatial ~~ memory
      verbal ~~ speed
      verbal ~~ memory
      speed ~~ memory


    • 模式適合度分析
      觀察值個數:145
      估計方法:ML
      疊代次數:273

      最小化函數檢定統計:
      模式
      model
      卡方檢定統計量
      Chi-square statistic
      自由度
      d.f.
      p-值
      p-value
      基準模式I 1638.466 276 0.000
      使用模式 358.789 242 0.000
      I:基準模式又稱獨立模式

      概似訊息準則:
      模式
      model
      概似值
      likelihood
      虛無模式(H0) -11453.195
      未限制模式(H1) -11273.801


    • 模式方程式參數估計(未標準化)
      潛在變數項:
      潛在變數
      latent
      顯性變數
      endogenous
      估計值
      estimate
      標準差
      std. err.
      Z-值
      z-value
      p-值
      p-value
      spatialt11.000
      spatialt20.4600.0905.0940.000
      spatialt30.2970.0575.1670.000
      spatialt41.1810.1796.6110.000
      verbalt51.000
      verbalt60.2930.02710.9940.000
      verbalt70.4140.03611.3680.000
      verbalt80.3980.0448.9930.000
      verbalt90.7170.06211.5700.000
      speedt101.000
      speedt110.7160.1066.7400.000
      speedt120.9500.1367.0000.000
      speedt131.7070.2417.0920.000
      memoryt141.000
      memoryt150.6900.1564.4200.000
      memoryt160.7450.1514.9250.000
      memoryt170.5110.1034.9800.000
      memoryt180.5150.1025.0590.000
      memoryt190.3250.0744.3810.000
      math_abilityt201.000
      math_abilityt210.2340.0356.5940.000
      math_abilityt220.4970.0736.8470.000
      math_abilityt230.5260.0707.4690.000
      math_abilityt240.2320.0356.6890.000
      迴歸項:
      依變數
      dependent
      解釋變數
      explanatory
      估計值
      estimate
      標準差
      std. err.
      Z-值
      z-value
      p-值
      p-value
      math_abilityspatial0.8210.3452.3820.017
      math_abilityverbal0.4920.1293.8120.000
      math_abilityspeed0.1320.0811.6360.102
      math_abilitymemory0.6960.2902.3950.017
      共變異數項:
      變數1
      variable 1
      變數2
      variable 2
      估計值
      estimate
      標準差
      std. err.
      Z-值
      z-value
      p-值
      p-value
      spatialverbal26.5445.7954.5800.000
      spatialspeed43.12510.6074.0660.000
      spatialmemory16.9074.4033.8400.000
      verbalspeed68.05717.3303.9270.000
      verbalmemory25.9447.0203.6960.000
      speedmemory52.35013.9263.7590.000
      變異數項:
      變數
      variable
      估計值
      estimate
      標準差
      std. err.
      t124.3913.893
      t214.7341.900
      t35.8740.761
      t436.5285.683
      t547.3446.775
      t63.7930.552
      t76.4580.980
      t814.6171.889
      t917.6922.762
      t10310.77444.454
      t11147.19321.447
      t12211.53332.622
      t13631.07799.951
      t1485.94511.079
      t1541.9775.398
      t1629.0203.996
      t1712.7731.780
      t1811.7821.675
      t199.6321.234
      t20221.32429.064
      t2114.0561.815
      t2254.6217.172
      t2340.8245.722
      t2413.0761.698
      spatial23.0805.461
      verbal87.62615.341
      speed250.91960.528
      memory30.50310.297
      math_ability25.02810.965


    • 模式方程式參數估計(標準化)
      潛在變數項:
      潛在變數
      latent
      顯性變數
      endogenous
      估計值
      estimate
      標準差
      std. err.
      Z-值
      z-value
      p-值
      p-value
      spatialt10.6972726NANANA
      spatialt20.49913140.09798015 5.0942093.502003e-07
      spatialt30.50711630.09814220 5.1671582.376803e-07
      spatialt40.68429300.10350973 6.6109053.819767e-11
      verbalt50.8057477NANANA
      verbalt60.81535950.0741660810.9936980.000000e+00
      verbalt70.83616080.0735510611.3684400.000000e+00
      verbalt80.69800800.07761329 8.9934080.000000e+00
      verbalt90.84732260.0732362311.5697190.000000e+00
      speedt100.6683704NANANA
      speedt110.68280680.10131005 6.7397741.586331e-11
      speedt120.71887090.10269074 7.0003482.553291e-12
      speedt130.73260420.10330071 7.0919571.322276e-12
      memoryt140.5118084NANANA
      memoryt150.50694820.11469188 4.4200889.866065e-06
      memoryt160.60683620.12321932 4.9248468.442668e-07
      memoryt170.61952180.12439004 4.9804786.342744e-07
      memoryt180.63817230.12615138 5.0587824.219436e-07
      memoryt190.50011720.11415170 4.3811631.180473e-05
      math_abilityt200.6560467NANANA
      math_abilityt210.62749590.09516851 6.5935244.295075e-11
      math_abilityt220.65586170.09579106 6.8467947.552403e-12
      math_abilityt230.72858360.09755383 7.4685288.104628e-14
      math_abilityt240.63815290.09539869 6.6893262.242007e-11
      迴歸項:
      依變數
      dependent
      解釋變數
      explanatory
      估計值
      estimate
      標準差
      std. err.
      Z-值
      z-value
      p-值
      p-value
      math_abilityspatial0.30482810.127983842.3817700.0172296544
      math_abilityverbal0.35628890.093454373.8124370.0001376032
      math_abilityspeed0.16161760.098809781.6356440.1019141595
      math_abilitymemory0.29714930.124048932.3954200.0166013377
      共變異數項:
      變數1
      variable 1
      變數2
      variable 2
      估計值
      estimate
      標準差
      std. err.
      Z-值
      z-value
      p-值
      p-value
      spatialverbal0.59023160.075975117.7687507.993606e-15
      spatialspeed0.56669260.085485256.6291273.376788e-11
      spatialmemory0.63718610.083298917.6493942.020606e-14
      verbalspeed0.45897570.080687705.6882991.283112e-08
      verbalmemory0.50181500.080859586.2060055.434833e-10
      speedmemory0.59837410.079849997.4937296.683543e-14
      變異數項:
      變數
      variable
      估計值
      estimate
      標準差
      std. err.
      t10.51381100.08201070
      t20.75086790.09685058
      t30.74283310.09623285
      t40.53174300.08272742
      t50.35077070.05019575
      t60.33518890.04874370
      t70.30083510.04564884
      t80.51278480.06625510
      t90.28204440.04403177
      t100.55328100.07914299
      t110.53377490.07777308
      t120.48322460.07452091
      t130.46329110.07337704
      t140.73805220.09514385
      t150.74300350.09554220
      t160.63174980.08699598
      t170.61619270.08588791
      t180.59273610.08427212
      t190.74988280.09609783
      t200.56960280.07479967
      t210.60624890.07826235
      t220.56984540.07482238
      t230.46916600.06576084
      t240.59276080.07698067
      spatial1.00000000.23663233
      verbal1.00000000.17506852
      speed1.00000000.24122352
      memory1.00000000.33756051
      math_ability0.14965830.06556625


    • 方程式路徑圖(彩色圖示暨標準化係數)


    • 方程式路徑圖(黑白圖示暨標準化係數)


  • 配適指標:
    • 絕對配適指標
      指標
      index

      value
      判斷準則
      criterion
      說明
      interpretation
      Fmin1.2372
      NCP116.7894越小越好Non-Central Parameter
      GFI0.8288> 0.95Goodness of Fit Index
      AGFI0.7878> 0.95調整GFI
      RMR10.9195< 0.05Root Mean Squared Residual
      SRMR0.0674< 0.08標準化RMR
      RMSEA0.0577< 0.06Root Mean Squared Error Approximation
      RMSEA P-值0.1571> 0.05
      ECVI3.2744越小越好Expected Cross-Validation Index


    • 增量配適指標
      指標
      index

      value
      判斷準則
      criterion
      說明
      interpretation
      CFI0.9143> 0.95Comparative Fit Index
      TLI0.9022> 0.95Tucker-Lewis Index,同Non-Normed Fit Index(NNFI)
      NFI0.781> 0.95Normed Fit Index


    • 精簡配適指標
      指標
      index

      value
      判斷準則
      criterion
      說明
      interpretation
      PNFI0.6848> 0.5Parsimonious Normed Fit Index
      PGFI0.6686> 0.5Parsimonious Goodness of Fit Index
      AIC23022.3909越小越好Akaike Information Criterion
      BIC23195.0414越小越好Bayesian Information Criterion
      SABIC23011.5088越小越好Sample-Size Adjustment BIC


    • 結構信度與平均萃取變異
      潛在變數
      Latent variable
      結構信度I
      CR
      平均萃取變異II
      AVE
      spatial0.69190.3652
      verbal0.89990.6437
      speed0.79430.4916
      memory0.73760.3214
      math_ability0.79560.4385
      I:一般建議CR > 0.7較合適
      II:一般建議AVE > 0.5較合適,AVE必須小於CR

    • 修正指標(> 3.84)
      左側
      LHS
      關係式
      operator
      右側
      RHS
      修正指標
      MI
      EPCI
      t10~~t2420.220979 26.98860595
      spatial=~t1316.345395 3.42705132
      spatial=~t1013.237412 -1.99630711
      t10~~t1212.551946 107.66530632
      spatial=~t1711.857517 -0.44472100
      speed=~t2411.298942 0.12109709
      spatial=~t24 9.634760 -0.55104735
      t14~~t18 9.111084 -9.51533876
      speed=~t21 8.273187 0.10676768
      verbal=~t21 7.842220 -0.19080144
      t1~~t13 7.498814 35.87362772
      speed=~t20 7.492335 -0.41040398
      t1~~t10 7.392686 -23.94582071
      speed=~t8 7.146754 0.07357608
      verbal=~t12 6.653365 -0.49492344
      math_ability=~t8 6.611190 0.12603871
      t6~~t12 6.598589 -7.39229577
      t6~~t11 6.587695 6.03018866
      spatial=~t16 6.220882 0.47979484
      t10~~t13 6.172634-133.78417060
      memory=~t11 5.988082 0.84351103
      t11~~t23 5.834516 -18.36798049
      t11~~t12 5.671219 -50.91466405
      t14~~t15 5.321954 12.81179067
      t13~~t17 5.286894 -20.71235036
      t2~~t17 5.141536 -2.87319942
      t8~~t9 4.890968 -3.76989395
      spatial=~t8 4.686180 0.23464545
      t12~~t16 4.523558 -16.46094197
      t19~~t20 4.448097 -8.82173044
      t18~~t23 4.432901 -4.51324725
      t3~~t13 4.390706 12.40382886
      t17~~t21 4.379930 -2.61319950
      memory=~t8 4.309314 0.17419047
      t5~~t9 4.286154 7.15993631
      t12~~t19 4.228339 -8.89685462
      t9~~t22 4.154071 6.29035204
      t3~~t22 4.125851 -3.31384264
      speed=~t9 4.098412 -0.06844909
      speed=~t22 4.055922 -0.14998835
      t1~~t16 4.022474 5.32962474
      t6~~t7 3.970328 1.16808139
      t6~~t18 3.939074 -1.30572483
      spatial=~t18 3.860518 0.24845804
      I:expected parameter change

    • 多變量常態分配檢定
      虛無假設:資料服從多變量常態分配
      檢定方法
      method
      w統計量
      w-statistic
      p-值
      p-value
      Shapiro-Wilk常態性檢定 0.7703 8.5226e-14
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