Questions tagged [structural-equation-modeling]

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.

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Difference between c-path, c'-path and indirect effect in mediation?

I am currently doing a parallel multiple mediator analysis with three mediators (ECVOM, SOCFAC, SCMEAN) using the PROCESS macro in SPSS. My DV is HAPMEAN and my IV is CUSTOM. I want to create a table ...
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Conversion from factor loadings to alpha scale reliability

For a power analysis of a structural equation model, I'm trying to follow the approach outlined in in the following article: ...
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Is it possible to run Confirmatory factor analysis with gsem on STATA with binary outcomes?

So far I have only seen an exmaple that involve counted number as the outcome, which has "poisson" as one of its option. My outcome variables are almost all binary, so I tried with "...
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How to use gsem when the independent variables are binary?

According to this website, "Binary—probit, logit, complementary log-log". But does the "binary" here mean independent variable or the latent variable (that is determined by the ...
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SEM model with binary outcome using LISREL

I am developing a SEM model for factors associated with dental caries. It has 48 observed variables and 13 latent variables. I have both independent and dependent latent variables in the model. ...
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Implementing a structural equation model in a within-between hybrid model

I am working on longitudinal data with three waves and have first utilized a hybrid probit regression model (within-between regression model). I have run the analyses in STATA using the following code:...
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Matrix Covariance Algebra

In the structural equation modeling (SEM) context, one of the modeling frameworks is called the reticular action model (RAM). In RAM, the observed variables (y) and latent variables (η) are combined ...
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Means-as-outcomes Regression Model with latent variable predictors at Level 2

I plan to estimate a structural equation model with several latent variables (e.g. importance of comfort when choosing a car) as predictors of a dependent variable which is a proportion: number of ...
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What are the assumptions of conducting a mediation analysis using structural equation modelling

What are the core assumptions when doing mediation analysis in structural equation modelling? I am estimating the classic mediation model using SEM in panel data in Stata with fixed effects (image ...
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Standardizing Factor Loadings SEM

I have the following structural equation model with latent variables f1 and f2 and observed variables x1-x6: ...
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Average variance extracted (AVE) with correlated error terms

after conducting a CFA I did some modifications to include correlated error terms (Error covariances) in my measurement models. Now I am wondering whether I need to apply a different formula für AVE / ...
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Some simplified equations to reflect structural equations mediation analysis

In panel data: Yi = [Yi1, ..., YiT]', Xi = [Xi1, ..., XiT]', (i=1, ..., n), I estimate a linear fixed-effects regression of mental health scores Yi as influenced by an unemployment shock (USit) as ...
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Moderation with higher-order factor - SEM

My colleague and I are wondering if we could use a product-indicators approach to compute moderations if the moderator is an higher-order factor. So my question is, how can I run a moderation with an ...
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Lavaan mediation + moderation + 2 X's

I'm trying to build a SEM that looks like the picture shown below: Where: $X$ and $X^2$ are the independent variables $Y$ is the dependent variable $M_1$ and $M_2$ are the mediators $W$ is a ...
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SEM model with multiple mediators and multiple independent variables in lavaan

I have cross-sectional data and I am trying to specify a model with multiple mediations. My independent variable (IV) is measured by a tool with 24 items, which make up 5 subscales (latent variables), ...
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What is “addition unique variance” in structural equation modeling?

I am studying confirmatory factor analysis and playing around with $\Omega\text{nyx}$. In the user guide, there is the following sentence: By default, a double-headed loop is created with each ...
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Mediation analysis: How to interpret an insignificant indirect while other effects are significant?

I performed a mediation analysis with package **lavaan** in R. My mediation analysis revealed: Path c is significant (total ...
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If I want to control for race in SEM, should I include race in the model, or should I run the model multiple times with 1 race category at a time?

I am running a SEM model. There is 1 independent variable, 1 mediator, and 2 dependent variables. All variables are continuous. I want to control for race (White, Black, Latino). To control for race, ...
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Bifactor model - Factor variances

I am estimating a bifactor model, i.e., a model including a general factor (G) and 4 specific constructs/factors (S1-4), all orthogonal (see below). The fit for the model is surprisingly good (CFI/TLI ...
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If the factor has only two indicators in CFA, the errors of those two indicators cannot be correlated?

I have heard that if the factor has only two indicators in CFA, the errors of those two indicators cannot be correlated. Is it true? if so, I'm wondering if the issue is due to only identification or ...
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What does it mean to indicate correlation in lavaan CFA?

I am an undergraduate psychology student and I've been doing basic statistical analysis for professors, post-grad students, etc for their work. I use R for almost everything I've recently faced myself ...
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Structural Equation Modeling without Latent Variables

I am learning and have used Structural Equation Models with latent variables, with measurement models and path analysis. It seems however, that I should be able to use them even without latent ...
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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 ...
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Q: R, SEM with lavaan, problems specifying correlations between subscales. ERROR: Warning, could not compute standard errors

I am currently working on running a SEM analysis in Lavaan and I am running into a few problems. Before running the full sem, I intended to run a CFA to replicate the psychometric testing done with ...
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What is the difference between using SEM and using mediation SEM on the same model?

Hope you're doing well :) With the following model: x --> m --> y, in which m could or could not be a mediator (this is one of the investigations' questions), is there a difference between ...
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Standardizing a variable in multigroup analysis- Solution for changing p-value?

I am conducting multigroup analysis in STATA with 990 participants to determine whether a proposed model differs across two groups (men and women). The model looks at the effect of variable A --> ...
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can I test for invariance if the base model has poor fit in CFA?

I am doing confirmatory factor analyses on a number of datasets where I want to confirm both factor structure and measurement invariance across groups, using lavaan in R. If the base model (before ...
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Can standardized path coefficients in SEM structure larger than 1

While I was conducting SEM on my model, I found 2 path coefficients are larger than 1 (one coefficient is 1.560, and the other one is -1.102). They should not be larger than 1 since they are all ...
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How does AMOS or other SEM/path analysis software estimate missing data?

I'm currently writing a paper as a hopeful publication. I'm using AMOS to run path models. But I think my question can apply when utilizing other path analytical software. I have one path model that ...
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Invariance for CFA in multiple groups over time with lavaan in R

Essentially, I am having trouble testing for invariance for a CFA in multiple groups over time. I am trying to do this with the lavaan package in R. I am following Little (2013) and attempting to do a ...
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In path analysis do you drop the non-significant pathways?

In path analysis do you drop the non-significant pathways? For example let's say we hypothesized this path model, but after testing this model the path from A to Y is a non-significant pathway. Then ...
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Model selection in path analysis? AIC, BIC, other fit measures

Running some path analysis models. I have one model with 6 variables and another model with 5 variables. The 5 variable model has an AIC = 30 and a BIC = 80, R Squared = .30 The 6 variable model has ...
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Should dummy variables be allowed to correlate (R code & data provided)

tl;dr: What is the difference between a regression model that allows its dummy variables to be correlated and one that doesn't do so? For example, how does that affect Standard Error of the regression ...
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Dependent variable with Poisson distribution in lavaan in R: how to deal with it?

I am planning to create a SEM model with lavaan. Most variables are normal, however, my dependent variable consists in a count of times and it has a Poisson distribution. Is there any Poisson ...
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25 views

Multi-group CFA analysis - two different outcomes

I have four first-order factors explained by one second-order factor. I am going to test the second-order factor across two different groups, one in Poland (group 1) and one in Spain (group 2). Also, ...
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Is it possible to use path analysis on data from split plot experimental design?

Assuming that the two treatments of a 3x2 factorial design study are dependent on one another (to some degree), is it acceptable to use a split plot experimental design? Alternatively, is it possible ...
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28 views

Bifactor-model in Mplus - warning message: PSI is not positive-definite

This question is about: When does the warning massage appear? I have a rather complicated model in Mplus that consists of three individual models. Each model consists of several manifest variables ...
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1answer
26 views

Chi Squared Fit Statistic in Structural Equation Models

I am interested in structural equation modeling. I am trying to get to the bottom of how $\chi^2$ is calculated for a structural equation model. I understand that outside of structural equation ...
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1answer
39 views

Structural Equation Modeling (SEM) with betareg in R

We have an SEM model and we were using Lavaan but we learned that the distribution of the residuals of one of the regressions is far from normal. The response variable in that equation is students' ...
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How to interpret “the flow of causality” for a variable in the middle of a path model?

I am struggling to interpret the relationships between variables in large path models. I have built a schematic path model that encapsulates my main issue. In the model below, how do I interpret the ...
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Latent Growth Curve Modeling and Model Choice

I am running an analysis of a clinical trial dataset. The research question is whether variable y influences the outcomes at each timepoint either as a main effect or in interaction with variable z (...
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Defining single indicators for CFA and covariance in Lavaan (R)

I am struggling with performing my very first confirmatory factor analysis (CFA) and structural equation model and I am already stuck. For reference, I am using the Lavaan package in R. I am ...
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SEM Lavaan output producing NAs

I've put together a fairly simple model, where X, Z, and Y are latent variables and I am trying to model an interaction between X and Z but when I do, the model does not seem to be converging. ...
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SEM with mixed and ordinal continues data, with missing values, with nonnormality

I have a dataset with missing values (over 10% missing), mixed ordinal and continuous variables, and non-normality. I am trying to fit a Structural equation model (SEM) using this dataset. Could I use ...
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Doing T-test across two data sets [closed]

So our paper is undergoing a second round of reviews and one of the reviewers asked the following question: "Add a t-test for wave 1 vs. wave 2. They won't be perfect, but if they are included as ...
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SEM with nonnormal data and missings in dataset

I am planning to conduct structural equation modelling and I am confused with all the different ways to handle the following situation: I have missings on my dependent variable, not on the other ...
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25 views

How to model this explicitly?

I have the following data: Levels of a specific microRNA, levels of two proteins that I have prior evidence are both regulated by this microRNA, and diagnostic stages of a disorder that is associated ...
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Interpreting Structural Equation Modeling using semPlot

I am getting confused on how to approach structural equation modeling. I have read some articles and textbooks about SEM using the lavaan and semPlot package though I'm getting mixed up with ...
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1answer
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DWLS estimator in lavaan & interpreting indirect effects

I performed SEM using lavaan with RStudio on a model that includes 1 categorical independent variable, 2 parallel mediators (ordinal), which are latent, and 2outcome variables, one of which is ordinal ...
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I am running a simple mediation model. How do I control for race, and if I do, will I loose statistical power?

I am running a simple mediation model in a path analysis framework using Mplus. The direct path in my model is grades (independent variable) predicting happiness (dependent variable). The indirect ...

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