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Results tagged with structural-equation-modeling
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user 9162
Structural Equation Modeling is a multivariate technique. It is based on formulating a set of linear relations between variables, some of which may be latent, and estimating the whole system, typically by analyzing the covariance matrix of the observed variables.
1
vote
2
answers
1k
views
Why are implied covariance matrices in SEM supposed to be nonpositive definite?
I read at this site some tips about what to do if the implied matrix is nonpositive definite. However, it's not clear to me why this is meant to be a problem.
Is the reasoning just:
- The population …
0
votes
1
answer
2k
views
SEM: saturated models versus just-identified models
I read in Kline (2016) p. 147 that
A just-identified structural equation model is identified and has the
same number of observations as free parameters.
I read here that
A saturated model is one in …
2
votes
1
answer
6k
views
Why does SEM not allow endogenous variables to covary with other variables?
This crossed my mind when I was reading this stata forum post, at which it is written:
SEM does not allow any endogenous variable to directly covary with any
other variable, only regression path …
6
votes
1
answer
3k
views
Why is RMSEA typically reported with a 90% confidence interval, and not 95%?
Kline (2016) writes that
[RMSEA] is usually reported in computer output with the 90% confidence
interval $[\hat{\epsilon}_{L},\hat{\epsilon}_{U}]$ where
$\hat{\epsilon}_{L}$ is the lower-boun …
5
votes
Accepted
Why is RMSEA typically reported with a 90% confidence interval, and not 95%?
Curran et al. (2003) write that:
It is common to report 90 percent confidence intervals for the RMSEA,
primarily because of the resulting direct link to hypothesis testing
based on the model …
2
votes
0
answers
43
views
SEM: Why is there no dependable connection between the size of SEM residuals and the type or...
Kline (2016) p. 278 writes
[Y]ou should know that there is actually no dependable or trustworthy
connection between the size of the residuals and the type or degree of
model misspecification. For exa …
3
votes
1
answer
2k
views
When does it make sense to apply SEM to experimental designs?
I've often seen it mentioned that while SEM is generally used in relation to non-experimental designs it can be used in relation to experimental designs too. For example, Kline (2016) writes that
…
2
votes
0
answers
535
views
Why is GLS scale invariant but not ULS in structural equation models?
Kline (2015) writes:
Two methods for continuous endogenous variables with multivariate
normal distributions include generalized least squares (GLS) and
unweighted least squares (ULS). The ULS method …
1
vote
0
answers
407
views
How should the Bollen-Stine bootstrap $p$-value be calculated?
Writing about an original test statistic $T_{ML}$, Nevitt and Hancock (2001) write on p356 that
The bootstrap-adjusted $p$ value is calculated as the proportion of
bootstrap model test statistics tha …
4
votes
1
answer
2k
views
Feasible to do hierarchical CFA with only two first-order factors?
Kline (2011) p249 writes:
To identify a hierarchical CFA model, there must be at least three
first-order factors. Otherwise, the direct effects of the second-order
factor on the first-order fa …
2
votes
1
answer
2k
views
CFA: Fix one loading per factor, or fix the variance of the factors?
I often see it noted that to help obtain an identifiable CFA solution you can either fix one loading per factor (usually fixing those loadings to 1), or else you can fix the variance of each latent fa …
5
votes
1
answer
17k
views
What does it mean to correlate residuals in SEM?
I have been reading a paper by Cole, Ciesla, and Steiger, which argues in many cases allowing residuals to correlate is justified. However, I am not entirely sure what it means for residuals to correl …
5
votes
2
answers
6k
views
Bootstrapping in SEM when the original sample size is small
I'm running a SEM in which I have several very positively skewed endogenous variables. Unfortunately, even when I log transform these variables they are still quite non-normal. Kline (2011) p64 writes …
4
votes
2
answers
4k
views
In CFA, does it matter which factor loading is set to 1?
I'd been previously taught that, aside from the fact that fixing a loading to 1 means you won't get a significance test on that loading, it was totally arbitrary which loading got fixed to 1.
However …
2
votes
1
answer
514
views
CFA: Significance testing on fixed parameters
In CFA for identification we fix one loading per factor, usually to 1. Then sometimes later on we are interested to do significance testing on the parameters. Below is some example AMOS output from Ar …