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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semPower: Accounting for Clustered Standard Errors in SEM Power Analysis with Fixed Effects Model
I am planning to analyse clustered data with a structural equation model and as I am planning on submitting my project as a registered report, I am first trying to do an in-depth power analysis (it is ...
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Latent growth curve model: The variance-covariance matrix of the estimated parameters (vcov) does not appear to be positive definite
I have run a latent growth curve model in R using lavaan and got the below warning. It would be good to hear suggestions on how to resolve this warning. The full output is below.
Note that I dummy-...
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EFA strongly suggests to extract a single factor. CFA 1-factor model fits badly. Why?
N > 1000. Average correlation in the matrix is like 0.8.
Parallel analysis, Minimum Average Partial, Scree plot, and Kaiser's criterion all unanimously suggested the extraction of a single factor. ...
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Constructing a structural equation model/causal graph
I would like to understand some intuitions behind the following causal graph/SCM.
Where as $X_1, X_2$ are expenditure on promotional activities.
My main interest lies in understanding the fact that ...
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Comparing factor scores between groups
I have participants who have taken an intervention and are being measured at two different time-points. It is expected that the intervention will improve their knowledge, attitude, confidence etc. and ...
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How to study what moderates a correlation?
I'd like to illustrate my objective with an example:
Imagine we have collected data on the height, weight, and level of sports activity (represented as either a continuous or categorical variable) ...
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Structural Equation Model design
Is it necessary in structural equation modeling (SEM) to incorporate all potential independent variables that could affect the dependent variable? Or is it acceptable to examine the influence of only ...
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R lavaan: quadratic regression of latent variables
Is there a way of specifying a quadratic regression between latent variables in lavaan? (Or in another R package for structural equation modeling?) That is, latent variable y, ...
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Latent growth curve model with a continuous time-invariant covariate, multi-group or covariate model?
A Latent growth curve model with a time-invariant covariant can be specified with (at least) two ways, by using the multigroup model approach or the "regression approach".
By regression ...
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Effect of robust maximum likelihood estimator in structural equation modelling when data is normal?
I understand that when data are nonnormal robust maximum likelihood estimator can be used.
I'm wondering are there any disadvantages of using a robust maximum likelihood estimator when the data are ...
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Is it possible to have an Indicator-spesific Trait factor model within a multiple indicator second order growth model?
I am running a multiple-indicator growth curve model over 7 time points.
One of my items has a large residual variance and seems to covary very well among themselves.
Thus, I assumed that it has a ...
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Structural equation modeling (latent growth models): robust estimators to handle outliers?
Can I use robust estimators (e.g., "MLM" and "MLR"estimator lavaan options) to overcome outliers within my sample, or should I remove outliers?
For context, I am modelling the ...
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Structural equation modelling in lavaan [closed]
I used factor analysis and structural equation modelling using lavaan in RStudio. Before adding the residual covariances and regression into the SEM model, the ...
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Path analysis for longitudinal data
I want to conduct a path analysis for longitudinal data with t = 13 (the model is presented below). Is it possible to make a path model for each individual at each time point? I am quite familiar with ...
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Goodness of fit of structural equation modelling
I am currently working on a structural equation modeling project using the lavaan package in R. The model satisfied all the goodness of fit tests (GFI, AGFI, CFI, ...
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How to interpret PLS-MGA’s results based on the significance of the corresponding group specific path coefficients
As a more general follow-up question to Elisa’s post on “[h]ow to interpret regression coefficients” when carrying out a PLS-structural-equation-modeling multigroup analysis (PLS-MGA), when comparing ...
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Robustness check in Structural Equation Modelling (SEM) in R
I have conducted SEM analysis in R and used Maximum Likelihood Robust estimator as my data are categorical and deviate from multivariate normality. when I submitted my manuscript, one reviewer asked ...
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Can you run a SEM on a correlation matrix only (without a covariance matrix)?
I have access to correlations between my variables of interest and the overall sample size. But I don't have standard deviations so I can't construct a covariance matrix. Can I still run a SEM on the ...
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Lavaan growth model: to treat endogenous variable as ordinal or continuous
I am modelling the trajectories of scores on two cognitive tests (i.e., PAL and SOS) measured at four time points. To do this I am creating separate latent growth curve models for each cognitive test, ...
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Structural Equation Modelling vs Mixed Effects Model
I have a question regarding what type of statistical analysis works best for my study design.
The research question is finding out what variables predict why a psychotherapy intervention is effective ...
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Modeling non-additive seasonal variable
Let's say I have some variable $x_{1}$ and some variable $x_{2}$ and I have the result of $y$ on a specific day/week/month/year. I believe $y$ is a random variable and its result is not very useful. ...
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Invariance coding for running a latent growth model running under partial (scalar or metric) invariance
I am running a second-order latent growth curve with 7 time points.
The model has a four indicator latent variables at the measurement level so I ran a longitudinal invariance test.
The model holds ...
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Linear Model, Identification of Structural Parameter
I'm reviewing the foundations of linear regression using Wooldridge's Econometric Analysis of Cross Section and Panel Data and Cameron and Trivedi's Microeconometrics : Methods and Applications. The ...
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Causal inference in DAGs and resulting structural equations
I am trying to understand the difference between the two modelling approaches described below that stems from the causal graphs.
Our goal is to causally measure the total treatment effect of our ...
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Serial multiple mediated model in lavaan not calculating standard errors, Z-values, and P values for defined parameters
I am trying to run the following model in Lavaan, in which AM, RM, and CU are latent variables. It also has three control variables (CV1, CV2, and CV3).
I have written the code that is included at ...
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Can my cycle-cut algorithm sample any DAG?
I am doing some computational simulations to validate a procedure involving structural equation models and causal inference. I wanted to sample from the possible space of DAGs on $n$ vertices. I can ...
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"The model is probably unidentified" in AMOS - how to fix this?
I am trying to fit a second-order factor in AMOS (where 'AA', 'AB', and 'AC' are thought to be facets of the higher-order factor 'AD'). I am getting the error message "Result (Measurement model)
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How much does model fit affect the analysis of an invariance test?
I am currently running a group invariance test with R, lavaan.
My total sample is 794. The results came out as the attached photo.
I understand that the chi-sq, CFI, and RMSEA all indicate that full
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Interaction between two binary variables in lavaan
I have two binary variables (X1 and X2, coded 0/1) as predictors in a growth model in lavaan. I want to understand their individual contributions and their ...
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Which effects to fix in SEM with two time points?
I am trying to fit a (to me relatively complex) SEM where I'm interested in two dependent variables measured at t2 and assume that this is explained through independent variables at t1. I have never ...
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Multivariate longitudinal/repeated measures models: change in latent variables vs. latent change
Researchers often employ multivariate longitudinal/repeated meatures models when they collect multiple measures ($k\in K$) on each of multiple occasions ($t\in T$) for each of multiple units ($i \in N$...
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When can Model fit indices (RMSE, CFI, TLI) be trusted?
I ran a three-level SEM and I have got perfect Model fit indices (RMSE=0, CFI=1, TLI=1). Data structure is households (hhid) nested inside the clusters (vilid), and being measured twice. The number of ...
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Need help defining the theoretical covariance matrix between a parameter and two distinct estimators
I have a problem that resembles SEM or factor analysis, but the indicators are estimators of the parameter, not empirical observations of random variables. The model is a one-factor model with two ...
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How to determine the number of estimated parameters in a structural equation model?
I'm trying run an a priori power analysis for an SEM and I need to know how many estimated parameters are included in the SEM. I'm having trouble understanding what exactly counts as an estimated ...
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Path tracing rules for nonlinear relationships
I'm learning about Wright's path-tracing rules, and because they deal with covariances it seems like they make the assumption that relationships between variables are linear. If we have nonlinear ...
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How to compute CI for reference group in multiple group SEM?
I am comparing several age groups on one latent factor with SEM in lavaan. The model shows strict invariance and i want to compare the latent means of the different age groups. To do so, i also want ...
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So significant serial mediating effect, but there is a significant mediating effect when the individual mediators are explored?
The statistical analysis used was PLS-SEM using WarpPLS.I have four variables, with 1 IV (W), 1 DV (Z), and 2 mediators (X and Y)
I was able to find that when run through W -> X -> Y -> Z the ...
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Binary and count variables as endogenous variables
I set up an APIM (actor-partner interdependence model) in R (lavaan).
No I'm facing the following issues:
Model: My endogenous variable is a count variable that follows a poisson-distribution.
Model:...
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define latent variables and measurment model in SEM
Does a latent variable in SEM need to be defined by validated scale or can you "imagine" one?
For instance, I work on school participation (defined in research by attendance to school and ...
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SEM : covariates and methodological questions regarding model simplification
I am new to SEM and have some methodological questions. Here is the model I would like run (LV = latent variable and OV = observed variables).
First, from the example I saw on the web, gender, age ...
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Interpretation of lavaan growth covariate parameters (effects on intercept and slope)
I am trying to interpret the output of the growth command with regressors. Here's the command, and the covariates are dummy coded 0/1:
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How to model casual relationship between time series in SEM?
I have some timestamped KPI which I need to identify casual relationship among.
During my literature review I came across Structural Equation Modelling (SEM). I have found some examples both in R and ...
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Analysis of longitudinal data with a change in DV - SEM, MANOVA or not possible?
I have a dataset in which a (latent) construct (e.g., math performance) is measured at different time points using different psychological tests.
The first data point is comparable to an assessment ...
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Marginalization of latents in SEM
As I understand it, there are tricks to marginalize-out latent quantities in structural equation models, but I'm having trouble finding explanations of how this is achieved that aligns with both my ...
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can someone explain the application of row.weights and sampling.weights in Lavaan?
I am trying to include the weight derived from Inverse Probability of Treatment Weighting into a structural equation model.However, it is unclear how it should be incorporated into the model and how ...
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Clarification Needed on Derivation in Judea Pearl's "Detecting Latent Heterogeneity" (2015)
I'm reading a paper by Judea Pearl titled "Detecting Latent Heterogeneity" from 2015, which can be found at this link: Detecting Latent Heterogeneity
I'm having trouble understanding a ...
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Consequences for not estimating autocorrelated residuals in a growth curve model
I am fitting a second order growth model with 7 time points on Mplus.
When I estimate the model with autocorrelated residuals in it
the model will not run because of identification issues.
(when I ...
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Is it necessary to report model fit indices for no latent variable model?
I built a moderated mediation model (Hayes Model 8 with no latent variables) for my research. Is it necessary to report model fit indices (e.g., CFI, Chi-squares) for this kind of research model?
If ...
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lavaan - sem with second order factor problem
I have a model in which I set relationships among different variables. One of them is a second-order factor.
However, I get the following problem when I try to run the analysis:
Warning messages:
1: ...
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is a threshold model on ordinal data ~ a link function? SEM OpenMx
Are anyone familiar with OpenMx's capacity for handling ordinal data in SEM using a link function like ordered logit or probit (Stata gsem does this)?
Some folks have highlighted issues with feeding ...
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