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workshop:index [2013/05/16 10:56]
10.45.84.252 created
workshop:index [2014/07/30 11:20] (current)
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 by [[http://​nd.psychstat.org/​research/​johnny_zhang|Zhiyong Zhang]] and [[http://​psychology.nd.edu/​faculty/​faculty-by-alpha/​ke-hai-yuan/​|Ke-Hai Yuan]] by [[http://​nd.psychstat.org/​research/​johnny_zhang|Zhiyong Zhang]] and [[http://​psychology.nd.edu/​faculty/​faculty-by-alpha/​ke-hai-yuan/​|Ke-Hai Yuan]]
  
-To be presented ​at the 78th Annual Meeting of the Psychometric Society in Arnhem, the Netherlands on July 22nd, 2013 and at the 121st Annual Convention of the American Psychological Association at Honolulu, HI, August 4, 2013. +To be presented at the 121st Annual Convention of the American Psychological Association at Honolulu, HI, August 4, 2013. 
 + 
 +[[workshop:​feedback|We welcome feedback on the workshop. Thanks.]] ​
 ===== Description ===== ===== Description =====
 Being capable of modeling latent variables and measurement errors simultaneously,​ structural equation modeling (SEM) has become one of the most popular statistical methods in social and behavioral research, where missing data are common, especially when data are collected longitudinally. Many procedures have been developed for modeling missing data in SEM, most of which are normal-distribution-based maximum likelihood (NML). However, NML estimates (NMLE) can be very inefficient or even biased when data have heavy tails or are contaminated. Being capable of modeling latent variables and measurement errors simultaneously,​ structural equation modeling (SEM) has become one of the most popular statistical methods in social and behavioral research, where missing data are common, especially when data are collected longitudinally. Many procedures have been developed for modeling missing data in SEM, most of which are normal-distribution-based maximum likelihood (NML). However, NML estimates (NMLE) can be very inefficient or even biased when data have heavy tails or are contaminated.
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   * Performance of test statistics   * Performance of test statistics
   * Missing data and influence of auxiliary variables   * Missing data and influence of auxiliary variables
 +  * {{:​workshop:​websem_apa_2013.pdf|Slides}}
  
 ===== Use of WebSEM ===== ===== Use of WebSEM =====
 The online software WebSEM is available at https://​websem.psychstat.org. By clicking the link, you will be directed to log in. If you have not registered as a user, please do so following the on-screen instruction. The online software WebSEM is available at https://​websem.psychstat.org. By clicking the link, you will be directed to log in. If you have not registered as a user, please do so following the on-screen instruction.
 +  * [[http://​www.youtube.com/​watch?​v=rdj1x_N3Rp4|Robust alpha]]\\ {{youtube>​rdj1x_N3Rp4}} 
 +  * [[http://​www.youtube.com/​watch?​v=GaRk3PmrBDo|Growth curve modeling]] \\ {{youtube>​GaRk3PmrBDo}} 
 +  * [[http://​www.youtube.com/​watch?​v=lbAsPum98DY|Mediation analysis]] \\ {{youtube>​lbAsPum98DY}} 
 +  * [[http://​www.youtube.com/​watch?​v=kLLNri-THy0|Multiple group analysis]] \\ {{youtube>​kLLNri-THy0}}
 ===== Example data sets ===== ===== Example data sets =====
-To be added+  * {{:​workshop:​alpha.txt|Robust alpha}}  
 +  * {{:​workshop:​robustsem.ex.txt|Growth curve modeling}} 
 +  * {{:​workshop:​mediation.txt|Mediation analysis}} 
 +  * {{:​workshop:​g2active.txt|Multiple group analysis}}
 ===== Recommended readings ===== ===== Recommended readings =====
   * Zhang, Z., & Yuan, K.-H. (2013). [[http://​nd.psychstat.org/​files/​Zhang%20&​%20Yuan,​%202013|Robust Coefficient Alpha for Non-normal and Missing data]].   * Zhang, Z., & Yuan, K.-H. (2013). [[http://​nd.psychstat.org/​files/​Zhang%20&​%20Yuan,​%202013|Robust Coefficient Alpha for Non-normal and Missing data]].
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   * Yuan, K.-H., & Zhang, Z. (2012). [[http://​nd.psychstat.org/​files/​Yuan%20&​%20Zhang%202012b.pdf|Structural equation modeling diagnostics using R package semdiag and EQS]]. //​Structural Equation Modeling: An Interdisciplinary Journal, 19//(4), 683-702.   * Yuan, K.-H., & Zhang, Z. (2012). [[http://​nd.psychstat.org/​files/​Yuan%20&​%20Zhang%202012b.pdf|Structural equation modeling diagnostics using R package semdiag and EQS]]. //​Structural Equation Modeling: An Interdisciplinary Journal, 19//(4), 683-702.
   * Yuan, K.-H., & Zhang, Z. (2012). [[http://​nd.psychstat.org/​files/​Yuan%20&​%20Zhang%202012a.pdf|Robust Structural Equation Modeling with Missing Data and Auxiliary Variables]]. //​Psychometrika,​ 77//(4), 803-826.   * Yuan, K.-H., & Zhang, Z. (2012). [[http://​nd.psychstat.org/​files/​Yuan%20&​%20Zhang%202012a.pdf|Robust Structural Equation Modeling with Missing Data and Auxiliary Variables]]. //​Psychometrika,​ 77//(4), 803-826.
-  * Yuan, K.-H., & Zhong, X. (2008). [[http://​nd.psychstat.org/​files/​Yuan%20&​%20Zh0ng%202008.pdf|Outliers,​ leverage observations and influential cases in factor analysis: Minimizing their effect using robust procedures]]. //​Sociological Methodology,​ 38//, 329-268.+  * Yuan, K.-H., & Zhong, X. (2008). [[http://​nd.psychstat.org/​files/​Yuan%20&​%20Zhong%202008.pdf|Outliers,​ leverage observations and influential cases in factor analysis: Minimizing their effect using robust procedures]]. //​Sociological Methodology,​ 38//, 329-268.
   * Zhang, Z., & Yuan, K.-H. (2012). [[http://​nd.psychstat.org/​files/​WebSEM_manual.pdf|WebSEM manual]]. [Software]. Available from https://​websem.psychstat.org.   * Zhang, Z., & Yuan, K.-H. (2012). [[http://​nd.psychstat.org/​files/​WebSEM_manual.pdf|WebSEM manual]]. [Software]. Available from https://​websem.psychstat.org.
workshop/index.1368716200.txt.gz · Last modified: 2014/07/30 11:20 (external edit)