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Questions tagged [sem]

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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lavaan: Correlation between each pair of variables [on hold]

I have several variables, say X1 to Xn, and I want to include correlation between each pair of them in my SEM (I use ...
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What statistical analysis should I use for comparing multiple variables at different time frames? (psychology experiment)

I'm planning a longitudinal psychology experiment where I want to compare levels of different variables over the course of an 8-week treatment. i.e. I want to see any increase/decrease in variable A, ...
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How to interpret contradicting path coefficients and f² effect sizes in Structural Equation Models (SEM)?

In the evaluation of my structural equation model with the PLS-SEM approach I have path coefficients between two constructs that are significant (p-value < 0.000) but the effect size f² is small ...
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29 views

Standard error for difference between two independent gains

I've calculated an effect size for the difference between two standardized pre-post differences of two independent groups of subjects. That is: $[Mean_{dif_{group~1}}/SD_{dif_{group~1}}]-[Mean_{dif_{...
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Path Analysis with multiple mediators and predictors

I recently started studying SEMs and path analysis in particular to analyze a data set. I have the following model, and I want to make sure I specified it correctly with ...
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Is it reasonable to include both principal component analysis (PCA) and Structural Equation Modeling (SEM) into a single regression?

Seems a bit silly to do both. Using PCA cleans up the way the model looks, bu reducing number of variables, but it seems like you would suffer an (unnecessary) loss of information.
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SEM 4 questions - testing linearity, sum score, number of variables, independent variables

For my master thesis I'm making a structural equation model. However, I do not have much experience with this. So here are some different questions. I read that one of the assumptions important for ...
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27 views

Estimating common slope across two traits for a parallel growth curve model

I am using a parallel growth curve model with 5 waves longitudinal data to evaluate correlated change among 2 traits. For models that showed the effects of correlated change among traits, I'm ...
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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-bound ...
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How do I do what I think would be a simple SEM?

I have the following data sets: miRNA levels in brain (one miRNA) protein levels in brain (two proteins) Clinical measure. It is known that the miRNA regulates the two proteins' translation from ...
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Does adding more than 1 dependent variable to SEM have purpose other than to control for correlation between dependent variables?

I am pretty new to SEM, so when I first saw a SEM model with 2 DVs, I wanted to know the difference between having 2 DVs and running SEM process twice for each DV. From what I understand, having more ...
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Markov property of manifest variables in longitudinal ESM

I am working on a longitudinal ESM model were the indicators are (highly) autocorrelated. This means that the classic cross-lagged models of panel data analysis cannot be used directly. I have ...
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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,...
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Multi-group SEM: what steps in measurement invariance

Sorry for asking a stupid question but I had been struggling for quite a while now. I'm not sure what steps to talke to evaluate a moderating effect in a path analysis model. I now have a path ...
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Do I report the pvalue of the standardized or unstandardized factor loading in CFA/SEM?

Using lavaan, for a simple CFA or SEM with measurement tools, you can use parameterEstimates(fit, standardized=TRUE) to get the standardized factor loadings for the ...
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Non-collapsibility issue in OR and mediation analysis with binary DV, binary mediator and 3-category IV

I have been looking for theory and software implementation to solve for non-collapsibility issue in mediation analysis with categorical DV and mediator (and IV). In my case, the DV and mediator are ...
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1answer
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EFA over time where changes in the factors are of interest

I am asking to find out if an idea that popped into my head is a real thing or just silly. EFA often presumes the data are static. I know there are forms of EFA that take time into account, but I ...
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Longitudinal CFA/SEM with autocorrelated/autoregressed indicators (in R, better with lavaan)

The problem is, I am trying to fit a multilevel factor model to highly autocorrelated (in fact, autoregressive) indicators. More specifically, I have multiple measurements (60-70) per person (5-10 ...
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49 views

Checking error covariances between indicator variables in sem/cfa

I'm learning SEM/CFA, and am currently following Beaujean's (2014) book on using lavaan. In the chapter where he talked about CFA and the number of indicator variables to have to ensure the model ...
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SEM resources from a linear model prospective

I'm starting a new project at work that requires theory and application of structural equation models, but my background is quite low in this area. I have a very good background in regression, linear ...
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190 views

Latent variable interaction: different number of indicators 4 vs 1

I am trying to calculate a latent variable interaction using the unconstrained product indicator approach (Marsh 2004) with double centering (Lin et al. 2010). My data: two latent predictor ...
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Why item discriminations are missing in IRT GRM, estimated as a part of the Structural Equation Model? [closed]

I have run a Structural Equation Model that has four latent constructs (FI, SC, EM and RB) in R. All of the factors are continuous. Meanwhile, indicators are all ordered categorical variables measured ...
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1answer
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Help moving forward after modIndices() in lavaan

I’m running a model in SEM using lavaan. I’ve really run into a puzzle I can’t quite seem to solve and I would love to tap into everyone’s expertise to help provide some direction. Below I’ve added ...
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How does explained variance in within level variables influence across-level-relations in multilevel SEMs?

Firstofall: I am sorry I cannot provide a minimal example code. I am trying my best to generalize the problem, but yet I just couldn't recreate it with dummy data. I try to provide any information ...
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Item response theory for continuous variables, and estimating standard error of measurement

I really like how traditional item response theory (IRT) packages tell you the standard error of measurement conditional on one's ability level, and from that, you can calculate the test information ...
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Question of Degrees of freedom negative in SEM [closed]

I have a "F_A_T_A_L E_R_R_O_R: Degrees of freedom is negative.", what can be the solution?
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Modelling latent variables: lavaan warning: covariance matrix of latent variables is not positive definite

I have 3 independent variables (linguistic, onk2_sc3 and dsk2_sc3) and one dependent variable (Reading) in SEM multigroups (3 groups) comparison: ...
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1answer
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Interpretation and formulation of SEM path coefficients?

Trying to interpret and write down my SEM results, but not sure if this is 1. correct and 2. well formulated. This is what my models and parameters look like (first unstandardized, then standardized): ...
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including dummy variable in SEM

Let us consider a regression model $y_i = \alpha+\beta x_i + \gamma d_i + u_i$ where $y_i$ and $x_i$ are scalar continuous variables and $d_i$ is a dummy variable that takes 0 or 1. (this is just a ...
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Predictive value of a predictor - model choice

I have been stuck on this for a while. I am supposed to find the "predictive value" of a predictor - entrance exam score. Together with the entrance exam score also grades from the first semester are ...
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1answer
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SEM Diagram and Measurement Invariance

Vandenberg & Lance (2000) explain that measurement invariance in SEM is important because the variance-covariance matrix of a group, $\Sigma$, and item scores, $X$, can be decomposed, such that $$...
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How to check SEM assumptions?

This question is related to SEMs that include latent variables e those that not include in lavaan package. SEM assumes normality/multivariate normality, but it is being very difficult to found a way ...
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29 views

Interpreting the latent growth model output

I started to go through this interesting structural equation model called latent growth curve model. When i go through some research articles that involved latent growth curve models, I found this ...
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MIMIC Model and standardization

I'm running a MIMIC model in MPlus with a dummy coded covariates and binary manifest variables. Which standardization should I use to calculate the ETS effect size for DIF, std, stdy, or stdyx?
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Why does my SEM ('lavaan') return covariance estimates for all pairwise variable combinations that were not specified in the model?

I specified the following model for SEM analysis using the 'lavaan' package in R. I want to specify a covariance between two observed variables (livestock and human occupancy). This is the only ...
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How to Determine Appropriate Values for Correlated Uniqueness in SEM Simulation?

I am trying to run a simulation of power/bias for a particular SEM, in which a number of correlated uniquenesses will need to be specified. I know how to determine the appropriate values of the ...
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Creating a weighted composite score from standardized lavaan latent beta weights that retains the scale of the original measures?

I did a latent factor analysis in Lavaan which had a good fit and gave me the following estimates of standardized beta weights for three latent variables called Eta1, Eta2, and Eta3. ...
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Acceptable CFI but poor TLI

I'm working on a path analysis using lavaan in R. Here is my model fit result: Chi square: >.05 Confirmatory Fit Index (CFI): 0.94 Tucker Lewis Index (TLI): 0.86 Root Mean Square Error of ...
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1answer
34 views

How exactly do I calculate the power in my SEM?

I am trying to calculate the power in my SEM analysis post-hoc. How exactly should I do this? What is the power for the R-squared result of IT-T2 and IT-T3? Background info: Sample size is 255. IT ...
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Is it appropriate/possible for me to use PLS regression for my problem?

Im currently writing a dissertation on the effect of cultural dimensions on technology acceptance. In order to collect data I have used a questionnaire with questions relating to technology acceptance,...
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Structural Equation Models: Tracing rule for error terms

Below is a graph together with my best guess for the system of equations resulting from (Wright’s) path decomposition underlying SEM. $cov_{obs}$ is the observed/sample covariance and $\beta$ and $\...
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When we test for factor invariance, does imbalance among groups affect fit indices?

My question is similar to this one: unequal group sizes in a multi-group CFA but applied to Explorative Structural Equation Model (ESEM) instead of CFA. In short: may group imbalance be a problem ...
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How to match different samples with different tests in a structural equations model? SPSS / AMOS

I am working on a study on hotels that analyzes the possible influence of the labor sastifacción (MSQ, 20 questions scale 1 to 5) in customer satisfaction (scale 1 to 5, questions that evaluate ...
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Estimating direct and total effects in path model (mediation)

I am testing mediation effects in this path model. How should I define the (1) direct and (2) total effects in this model? Is the below correct? (1) Direct= c1*c2 (2) Total= (c1*c2)+a1*d21*b2
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Path analysis with two mediators and reciprocal causation

I am trying to fit a path analysis which predicts a participant's binary choice of either a safe or a risky option. I am using a 2x2 design which includes multiple mediators. My big question is how to ...
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Mimic model in panel data

I'm working on my PHD, and i have panel data for diseases (i) and time(t), i want to apply mimic model ( multiple indicator multiple cause model) on these data . 1- is it possible to apply random ...
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Testing parameter significance vs model fit

In one of our studies we test a mediation hypothesis in a longitudinal (it's actually panel data) study with 4 measurement waves. We test a setup similar to one outlined by Cole & Maxwell (2003) ...
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Analysing panel data - looking for hypothesized mediation and moderation effects

Good afternoon, I'd like to ask you for some help in finding a (hopefully citable) way of analyzing panel data when looking for mediation and moderation effects. Problem I have is that my measured ...
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1answer
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Are direct effects between latent variable indicators ever appropriate?

I have a longitudinal structural model regressing 1 endogenous latent variable at Time 2 on 4 exogenous latent variables at Time 1. The modification indices in Mplus suggest including a direct effect ...
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Interpretation of Sequential (Serial) Mediation Effect (vs. Cross-lagged panel model)

I would like some clarification on the interpretation of the significant indirect effect involving "d21", when the two mediators (M1, M2) are the same constructs measured at two consecutive time ...