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題名:分析方法與交乘項策略組合對潛在交互作用及二次效果估計之評估
書刊名:中華心理學刊
作者:陳淑萍余麗樺 引用關係鄭中平 引用關係
作者(外文):Chen, Shu-pingYu, LifaCheng, Chung-ping
出版日期:2008
卷期:50:4
頁次:頁447-472
主題關鍵詞:結構方程模型潛在交互作用效果潛在非線性效果Latent interaction effectLatent nonlinear effectStructural equation modeling
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(1) 博士論文(1) 專書(0) 專書論文(0)
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  • 共同引用共同引用:0
  • 點閱點閱:94
實徵研究上,非線性關係常為研究者所關切,發展潛在變項間交互作用與二次效果等非線性效果之估計有其重要性。本研究以模擬方式,評估中心化限制式方法、Jaccard與Wan程序、部分限制式方法及未限制式方法等四種利用引進交乘項的方法,搭配單一配對、兩兩配對及所有配對型式不同交乘項策略下,對潛在交互作用模型與潛在二次模型估計之影響。結果顯示,四種方法與交乘項策略對估計影響不大,但部分限制式方法於三種配對組合、未限制式方法於兩兩配對與所有配對組合,在適當解比率與參數估計評估表現皆較其他組合差,以小樣本或外生潛在變項負載量低時尤為明顯。
In conducting empirical research, researchers are often interested in nonlinear relationships. Thus, accurately estimating latent interaction and quadratic effects is of great importance. This research aims to evaluate latent interaction and quadratic effects by means of the Monte Carlo method. Performances of all possible combinations of four product indicator based analysis methods with three product strategies are examined. The four approaches used in this study include the centered constrained approach, Jaccard and Wan's procedure, the partially constrained approach, and the unconstrained approach, while the three product strategies are one pair, matched pairs, and all pairs. The results indicate that different approaches and product strategies have little effect on the estimates, but the partially constrained approach and the unconstrained approach (except for the one-pair strategy) produce fewer fully proper solutions, more bias and greater root mean square error for smaller sample sizes or poor reliability of the indicators.
期刊論文
1.Cortina, J. M.、Chen, G.、Dunlap, W. P.(2001)。Testing Interaction Effects in LISREL: Examination and Illustration of Available Procedures。Organizational Research Methods,4(4),324-360。  new window
2.Algina, J.、Moulder, B. C.(2002)。Comparison of methods for estimating and testing latent variable interactions。Structural Equation Modeling,9,1-19。  new window
3.Jaccard, J.、Wan, C. K.(1995)。Measurement Error in the Analysis of Interaction Effects between Continuous Predictors Using Multiple Regression: Multiple Indicator and Structural Equation approaches。Psychological Bulletin,117,348-357。  new window
4.Klein, A. G.、Moosbrugger, H.(2000)。Maximum Likelihood Estimation of Latent Interaction Effects with the LMS Method。Psychometrika,65,457-474。  new window
5.Wall, M. M.、Amemiya, Y.(2001)。Generalized Appended Product Indicator Procedure for Nonlinear Structural Equation Analysis。Journal of Educational and Behavioral Statistics,26,1-29。  new window
6.Little, T. D.、Bovaird, J. A.、Widaman, K. F.(2006)。On the Merits of Orthogonalizing Powered and Product Terms: Implications for Modeling Interactions among Latent Variables。Structural Equation Modeling: A Multidisciplinary Journal,13(4),497-519。  new window
7.Klein, A. G.、Muthén, B. O.(2007)。Quasi maximum likelihood estimation of structural equation models with multiple interaction and quadratic effects。Multivariate Behavioral Research,42(4),647-673。  new window
8.Kenny, D. A.、Judd, C. M.(1984)。Estimating the Nonlinear and Interactive Effects of Latent Variables。Psychological Bulletin,96(1),201-210。  new window
9.Marsh, H. W.、Wen, Z.、Hau, K. T.(2004)。Structural Equation Models of Latent Interactions: Evaluation of Alternative Estimation Strategies and Indicator Construction。Psychological Methods,9(3),275-300。  new window
10.Williams, L. J.、Edwards, J. R.、Vandenberg, R. J.(2003)。Recent advances in causal modeling methods for organizational and management research。Journal of Management,29(6),903-936。  new window
11.Lee, S. Y.、Zhu, H. T.(2000)。Statistical Analysis of Nonlinear Structural Equation Models with Continuous and Polytomous Data。British Journal of Mathematical and Statistical Psychology,53(2),209-232。  new window
12.Arminger, G.、Muthén, B. O.(1998)。A Bayesian Approach to Nnonlinear Latent Variable Models Using the Gibbs-Sampler and the Metropolis-Hastings Algorithm。Psychometrika,63,271-300。  new window
13.Ping, R. A. Jr.(1996)。Latent variable interaction and quadratic effect estimation: A two-step technique using structural equation analysis。Psychological Bulletin,119(1),166-175。  new window
14.Bentler, Paul M.、Chou, Chih-ping(1987)。Practical Issues in Structural Modeling。Sociological Methods and Research,16(1),78-117。  new window
15.Moosbrugger, H.、Schermelleh-Engel, K.、Klein, A.(1997)。Methodological Problems of Estimating Latent Interaction Effects。Methods of Psychological Research Online,2(2),95-111。  new window
16.Algina, J.、Moulder, B. C.(2001)。A Note on Estimating the Jöreskog-Yang Model for Latent Variable Interaction Using LISREL 8.3。Structural Equation Modeling,8,40-52。  new window
17.Bauer, D. J.(2005)。A Semiparametric Approach to Modeling Nonlinear Relations among Latent Variables。Structural Equation Modeling,12,513-535。  new window
18.Lee, S. Y.、Song, X. Y.、Poon, W. Y.(2004)。Comparison of Approaches in Estimating Interaction and Quadratic Effects of Latent Variables。Multivariate Behavioral Research,39,37-67。  new window
19.Lee, S. Y.、Zhu, H. T.(2002)。Maximum Likelihood Estimation of Nonlinear Structural Equation Models。Psychometrika,67,189-210。  new window
20.Busemeyer, J. R.、Jones, L. E.(1983)。Analysis of Multiplicative Combination Rules When the Causal Variables are Measured with Error。Psychological Bulletin,93,549-562。  new window
21.Wall, M. M.、Amemiya, Y.(2000)。Estimation for Polynomial Structural Equation Models。Journal of the American Statistical Association,95,929-940。  new window
圖書
1.Bollen, K. A.(1989)。Structural Equations with Latent Variables。New York:John Wiley & Sons。  new window
2.Jöreskog, K. G.、Yang, F.(1996)。Nonlinear Structural Equation mModels: The Kenny-Judd Model with Interaction Effects。Advanced Structural Equation Modeling: Issues and Techniques。Mahwah, NJ。  new window
3.Tate, R. L.(1998)。Effect Decomposition in Interaction and Nonlinear Models。Interaction and Nonlinear Effects in Structural Equation Modeling。Mahwah, NJ。  new window
4.Ping, R. A.(1998)。EQS and LISREL Examples Using Survey Data。Interaction and Nonlinear Effects in Structural Equation Modeling。Mahwah, NJ。  new window
5.Wood, P. K.、Erikson, D. J.(1998)。Estimating Interaction and Nonlinear Effects with SAS。Interaction and Nonlinear Effects in Structural Equation Modeling。Mahwah, NJ。  new window
6.Milliken, G. A.、Johnson, D. E.(1989)。Analysis of Messy Data, Vol. II。Analysis of Messy Data, Vol. II。Belmont, CA。  new window
圖書論文
1.Bollen, K. A.、Paxton, P.(1998)。Two-stage Least Squares Estimation of Interaction Effects。Interaction and Nonlinear Effects in Structural Equation Modeling。Mahwah, NJ:Lawrence Erlbaum Associates, Inc.。  new window
2.Boomsma, A.、Hoogland, J. J.(2001)。The robustness of lisrel modeling revisited。Structural equation models: Present and future. A Festschrift in honor of Karl Joreskog。Chicago, IL:Scientific Software International。  new window
3.Neale, M. C.(1998)。Modeling Interaction and Nonlinear Effects with Mx: A General Approach。Interaction and Nonlinear Effects in Structural Equation Modeling。Mahwah, NJ:Lawrence Erlbaum Associates, Inc.。  new window
4.Schermelleh-Engel, K.、Klein, A.、Moosbrugger, H.(1998)。Estimating nonlinear effects using a latent moderated structural equations approach。Interaction and nonlinear effects in structural equation modeling。Mahwah, NJ:Lawrence Erlbaum Associates, Inc.。  new window
5.Marsh, H. W.、Wen, Z.、Hau, K. T.(2006)。Structural equation models of latent interaction and quadratic effects。Introduction to structural equation modeling: A second course。Mahwah, NJ:Erlbaum。  new window
 
 
 
 
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