Structural Equation Modeling is a multivariate technique popular in social sciences. 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.

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Observed variables in R's lavaan

I am running a SEM on lavaan in R. The model consists of latent variables [N1 to N3], two dummy choice variables [du1 and du2] and observed satisfaction variable [SV] (beside the observed variables). ...
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9 views

Performing CFA & Structural Models

I have developed a conceptual framework based on literature. The conceptual framework comprises antecedents and consequences. The antecedents factor 1, factor 2 and factor 3 affects factor 1 and ...
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14 views

whether PCA be conducted for a single dimension or simultaneously across multiple dimensions [closed]

whether PCA be conducted for a single dimension or simultaneously across multiple dimensions whether CFA be conducted for a single dimension or simultaneously across multiple dimensions I have gone ...
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13 views

Is it possible to combine bayesian SEM with PLS SEM?

I have already read some books about both two structural equation models. It seems both SEMs are suitable to the situation with small observations and large variables. I assume to use combine both ...
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13 views

SEM for Non-Normal Ordinal Data

In short, I conducted a satisfaction survey in which surveyees are required to answer on a satisfaction scale from 1 to 7: 285 observations, 37 satisfaction variables. Here is an example of what the ...
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13 views

Estimating the parameters of a model, which method should I use?

I am trying to estimate a system of macroeconomic (simultaneous) equations, and I've learned about the 'existence' of various methods including Structural Equation Models, Simultaneous Equations ...
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10 views

How to test measurement invariance with PLS?

I have two questions about structural equations modeling: To perform comparisons of model estimates for different groups (3 clusters), do I always have to analize measurement invariance first? If ...
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10 views

How do I convert unstandardized RMR estimates into standardized RMR estimates?

I am having difficulty turning unstandardized RMR estimates from AMOS software output in a SEM into standardized estimates to enable suitable interpretation. Can someone give me advice on where to ...
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15 views

Why did fixing the covariance value cause AMOS to mis-estimate variance?

I have 100 data points on two variables, a and b. The correlation between the two is .3 and the SD is 1. When I run the ...
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7 views

What's the minimum number of measured variables required when fitting a one latent variable model?

I am envisaging a situation in which I have designed a small questionnaire, and want to assess whether the measured variables are measuring the same thing. I'm not really interested in practical tips ...
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12 views

Differentiating strength of relationships between categorical and continuous variables in SEM?

I'm currently planning an SEM study designed to investigate attitudes toward energy technologies. My past research has suggested that the persuasive effect of positive/negative information is minimal, ...
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139 views

Optimal sampling strategy for EFA, CFA and SEM

I'm wondering what should be the optimal sampling strategy for my dissertation research. I have four data sources (two open source software projects meta-repositories and two global startup ...
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9 views

parameter estimation in bivariate autoregressive sem with individual heterogeneity - troublesome likelihood surface

I am working with models for panel data of individuals, wherein: my latent variables Yt= $\beta$Yt-1+Ai+Q Individuals level of the process A~N(l,h) Innovation of the latent Q~N(0,q) observed variables ...
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1answer
100 views

ML vs WLSMV: which is better for categorical data and why?

I was wondering which is a better estimator to use for categorical data: ML or WLSMV. I saw on a discussion on the Mplus website that they recommend WLSMV for categorical data but didn't explain why. ...
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57 views

power/sample size for a complex set of equations

I run an experiment in which several teams perform several tasks each (not all teams perform all tasks, but in general, I can make sure that enough teams perform any given task, and that each team ...
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50 views

Structural equation model: Bootstrap, Bayesian statistic or rescaling binary data to deal with small sample size?

I’m trying to solve a SEM. Mi model includes 4 latent variables and 11 observed variables. My data is binary. Question 1: I just have 47 observations and in the literature a sample size over 150-200 ...
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18 views

Any thoughts in PLS as an alternative to SEM if you have a small sample size?

I have put a question on here before re SEM and small sample sizes. I have 3 factors each with 3 manifest variables each. I only have 90 records. I want to find out the amount of covariance between ...
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1answer
126 views

Transforming a relationship from quadratic to linear

Assume that I'm running a path analysis and I have discovered that certain relationships, empirically, are quadratic rather than linear. In order to model the data as such, I want to transform the ...
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39 views

Sample size for SEM. What are the alternatives

I have 3 latent variables with 3 measures each. I understand the conventional sample size would be 15 participants per measure (i.e. 9 x 15 = 135). I have 85 participants and don't think I will have ...
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2answers
115 views

A question on SEM and path analysis

For my PhD dissertation, I am offering a conceptual model on teacher professional development. My model has one mediator. I wonder if I can test the mediation through Baron and Kenny's procedure or ...
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1answer
109 views

How to do Simple Confirmatory Factory Analysis/SEM in R?

I have a data set consisting of 166 observations on 24 variables (a1, a2, a3, ...
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1answer
176 views

Moderation with latent variables in Stata 13

I am wondering if anyone has insight regarding the creation of interaction terms (moderators) in a model with latent predictors using Stata 13 - SEM. I have what I want to be the moderator set up ...
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30 views

Delta method for a two equation system

I want to estimate a nonlinear coefficient from a 2 equations system and use the delta method to calculate the standard errors for inference. \begin{align} y_{i1} &= \alpha_{0} + ...
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1answer
120 views

Material on Structural Equation Modelling (SEM)

I've little background on SEM. Now I want to focus on its theoretical aspects like statistical model, model estimation and model evaluation. The seminal book on this topic is by Bollen: Structural ...
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46 views

Is Bayesian structural equation modelling better than maximum likelihood with smaller sample sizes?

Does using the bayesian estimator to complete SEM in Mplus mitigate some concerns with a limited sample size (n=120). I.e is this approach preferred over using the traditional ML estimator with ...
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1answer
70 views

What happens when SEM is conducted with a rank-based DV?

Can SEM be conducted with a rank-based dependent variable? If so, which software package would be the way to go? Obviously, you'll get LISREL output and such, but I'm concerned as to how the ...
3
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1answer
58 views

Inconsistent delta.chisq.scaled using Lavaan and semTools?

I've recently been using Lavaan and semTools to test for measurement invariance in confirmatory factor analysis (CFA) models and I noticed an (apparent) inconsistency in a calculation that confused ...
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31 views

Is there a method for testing follow-up individual factor and item invariance using the lava an or semTools packages in R?

I've found the "measurementInvariance" command from the semTools package EXTREMELY helpful recently, but now I am wondering if there is a way to conduct follow-up factor-level and item-level ...
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87 views

How to extract “MLR” fit measures generated by the Lavaan package of R

I am estimating some Confirmatory Factor Analysis (CFA) models using the Lavaan package and I hoping to extract the fitMeasures to export out of the model to a spreadsheet. This is easily done using ...
4
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1answer
207 views

Good internal factor structure but poor cronbach alpha?

I am running a CFA and getting good fit indices (CFI = .99, RMSEA = .01) for a uni-dimensional scale. However, when I test for internal consistency, I get poor Cronbach alphas (alpha = .6). I have ...
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41 views

Lisrel: Goodness-of-fit with FIML and missing data

When doing a missing-data analysis with FIML in Lisrel, I don't get a lot of goodness-of-fit statistics. I have discovered that you can calculate the fit-indices using the Chi-Square from an ...
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2answers
121 views

Difference of 'centers' of 2 non-normal samples with Mann-Whitney test

I have 2 non-normally distributed samples of different sizes (N1~=N2). To evaluate whether there is a significant difference between these samples, I used the Mann Whitney U test (...
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44 views

SEM using composites or indicators?

I am new to SEM. I am analyzing a dataset with five constructs and 21 indicators. I found there could be two ways to run the structural model in AMOS. One is to include all the measured indicators in ...
3
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1answer
160 views

Covary two dummy variables in SEM?

I am running a structural equation model (SEM) in Amos 18, and I want to test the impact of marital status on several latent variables. Marital status is nominal, so I created three dummy variables: ...
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101 views

Path analysis, sample sizes, and alternative analysis

I am examining how English ivy affects the occurrence of a salamander species under cover objects (e.g., logs). Soil moisture is assumed to be the major factor that affect their occurrence. My ...
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123 views

STATISTICA 12 for SEM data analysis [closed]

I'm a graduate student pursuing Ph.D. in Information Systems. My dissertation research involves using structural equation modeling (SEM-PLS) as a main data analysis method. After comparing various ...
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114 views

How to get confidence intervals for specific indirect effects in Amos?

Say I have an SEM model with 1 predictor variable (IV), 2 mediators (MV1, MV2) and 1 dependent variable (DV). Amos reports combined indirect effects for an IV on a DV. So the combined indirect effect ...
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147 views

Interpreting a mediation model with binary outcome

I have a mediation model with two continuous mediators (m1; m2), a continuous input variable (x) and a dichotomous output variable (y). The two mediators are different mechanisms of the input ...
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1answer
47 views

What is the substantive meaning of scalar invariance?

I understand that scalar invariance, in the context of Structural Equations Modeling (SEM), is having the intercepts for observed variables loading on the same latent variable be invariant across ...
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42 views

Transforming data to meet regression assumptions for SEM including interaction effects

If you are fitting a SEM and wish to add an interaction effect between two variables, I understand that you convert the variables to z-scores, multiply them together and insert this new variable into ...
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56 views

Question about regression coefficients (confidence intervals & bootstrapping)

In my SEM I estimate effects of risk factor $x$ on symptoms $y_1$ and $y_2$ (many more, but this is just to present my particular problem). $y$ have different distributions, some of $y$ are quite ...
0
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1answer
47 views

Composite variables in SEM

I am doing an analysis of latent constructs. I was wondering whether it was acceptable to use composite variables given that the measures associated with each of the latent constructs uses up to 80 ...
3
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379 views

Comparing SEM software apps: AMOS vs Stata vs Mplus vs R -— opinions please? [closed]

I have AMOS and Stata, and I have a colleague who has Mplus (and I'd rather not ask the colleague to run my data for me). I recently discovered that Stata has SEM capabilities. I looked online, but I ...
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122 views

Control variables in SEM

I want to add control variables to a SEM model, because I expect for example that age affects both your level of trust in the police (higher for younger persons because of naivety) and your ...
2
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1answer
254 views

SEM: Robustness of fit indices (CFI, TLI and RMSEA) when data are non-normal

Because my data is not normally distributed, I used the Maximum Likelihood Robust Estimator (MLR) in Mplus. Now I know that this estimator produces a robust chi-square-statistic and robust standard ...
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179 views

Doing CFA on a known theoretical model, but having problems with convergent and discriminant validity

I did a survey based on the UTAUT model / theory with standard questions used. The N was 150. I am trying to validate the model for my survey with structural equation modeling (via the AMOS software). ...
3
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1answer
54 views

What are operational (true) validities?

In the article Oh & Berry (2009), p. 1506, in the note for Table 2, a certain statistic is used: "Operational (true) validity is the LISREL estimated correlation corrected for measurement error ...
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0answers
68 views

Multiple mediation model suitable?

Objective To test which base of power performs best in the adaptation process [of something] in a buyer-supplier relationship To understand that, I shall give a quick explanation about what bases ...
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1answer
96 views

Should a non-significant adjustment variable be kept in a regression model? [duplicate]

I'm working with a structural equation model to study influenza infection risk. As age is a known risk factor to explain infection, I therefore adjusted my infection outcome on the subjects age class. ...
5
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1answer
348 views

SEM: Collinearity between two latent variables that are used to predict a third latent variable

In some structural equation models that I use in my bachelor thesis, there is a substantial correlation between two latent variables that are used to predict a third latent variable. Now I know there ...