Talk:Structural equation modeling
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[edit] SEM vs Graphical Models, Bayesian networks
Could someone please explain the difference?
[edit] contributions
Hi, I think the article is excellent and am disturbed by the clean-up indicators at the beginning that make it appear that there are serious problems. Nothing is perfect; however I was greatly informed by the clear writing, which I felt was not too technical and perfectly understandable. --Littleelf (talk) 11:31, 31 March 2008 (UTC)
Hi, I would like to invite authors to contribute articles to this entry. Some things that can be included are:
1. Lesson plans for teaching SEM 2. List of good books on SEM 3. Key, "must read" articles
Hello,
It seems that emphasizing the difference between linear multiple regression and SEM is important for this article. Does anybody know more about this? To be frankly, I cannot see any urgent needs to state that y_i is determined by y_0,1,2, ..., n (except for i) in SEM. What can be the situations that can be described better with SEM than with linear regression?
I'll be working on this page at my leisure time, if any, as this is my major research topic. What would be the best way to incorporate path diagrams into Wikipedia? I can do matrices with MathML, or whatever interface Wikipedia has for math, but the path diagrams would obviously have to go as graphics files.
Stas Kolenikov
[edit] "SEM has several important advantages ..."
"SEM allows for multiple dependent variable, whereas OLS regressions allows only a single dependent variable." I would say no: SEM is a model where as OLS is an estimation technique. OLS can be used for SEM.
"SEM allows simultaneous tests of multiple groups". I do not understand this: OLS can be used for multivariate regression analysis... In this type of model/analysis there are several response/dependent variables.
"SEM accounts for measurement error, whereas OLS regression assumes perfect measurement." In multivariate regression analysis you have Y=XB+U, and the Y is assumed to be confounded with measurement error (the U's).
- fnielsen 11:24, 10 March 2006 (UTC)
To fnielsen: Most of the notes you made are SEM jargon.
OLS cannot be used for SEM because of the measurement error. Or rather the class of SEMs to which OLS is applicable is very narrow (recursive/trinagluar models where all variables are observed; those are not very interesting).
Multiple groups means that you might have different parameters for different subpopulations. In OLS, you would model that through interactions. In SEM, however, there are way more parameters than just slopes, so you may have say the same loadings, but different measurement error variances between males and females. Multiple group comparisons are then based on nested hypotheses where you allow some of the model parameters vary between groups.
OLS assumes X's are fixed. Typically, that's too much a luxury to assume with SEM where most of the observed variables are truly random variables and contain measurement error.
GLM means generalized linear model to most statisticians; using it for general linear model is rather awkward, I'd say.
- Stas Kolenikov 16 March 2006
[edit] Category
Should this page have another category? I thought I remembered reading that a page should have at least two categories but cannot find the policy at the moment. Any suggestions? --Kenneth M Burke 01:39, 2 August 2007 (UTC)
[edit] POV
The introduction I think might have some problems with point of view, i.e. that SEM is confirmatory rather than exploratory. Not to mention, I think it is plagiarized from another website. Not being an expert and where parts of the introduction does cite sources, I did not put a POV template on the page. This being said, maybe a more textbook language common to mathematics and research methods would be better than the "confirmatory" and "exploratory," which sounds like its from a bad sci-fi movie that didn't do its homework. Just casual thoughts and suggestions. --Kenneth M Burke 01:32, 20 August 2007 (UTC)
- Well, after doing my own homework, that's what they call it. But, the amount of information that one can find on both exploratory and confirmatory SEM I think certainly shows problems with POV in the article. --Kenneth M Burke 01:43, 20 August 2007 (UTC)
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- I've come to strongly believe that the information on SEM as primarily confirmatory is biased. Even the most basic of introductory texts note that it is not exclusively confirmatory (Kline, 2005, p. 9, New York: Guilford Press, Principles and practice of Structural Equation Modeling). We need remember that SEM is not a single method, that there are many means and methods for SEM. --Kenneth M Burke 18:00, 28 October 2007 (UTC)
[edit] SEM- Censored data, categorical data, and Likert scale
Hi, Though not an expert in SEM, I have developed an interest in the subject and The SEM softwares. I will recommend that,That the article include more information on censured Data and Categorical data.
The main contention is when do we consider a Likert scale to be continous? Can we Indexes in SEM? Wadson12 13:58, 9 November 2007 (UTC)
