Yes, you can use even if one of your dependent variables is a dummy variable (binary). SEM can handle both continuous and categorical (including binary) variables.
@@AGRONInfoTech does this specification consider the correlation between errors? For instance in stata to get estimation coefficient equivalent to ivregress you must specify cov(e*e), is it the same in this package?
@@chiaras2274 In the lavaan package for R, you can specify correlations between the errors of different equations (residual covariances) directly in the model syntax. This is similar to specifying cov(e*e) in Stata to account for Correlationterms. For example: # Define the model with correlation term model
You can achieve this while specifying the model and creating the mod.id object. Simply use the desired names for the latent variables instead of "EA" and "YC." For other variables used from the dataset, you can rename them either in the Excel sheet before importing the data or by defining the column names after importing it.
Lavaan supports a wide range of models, including confirmatory factor analysis (CFA), path analysis, structural equation modeling, and growth curve modeling. It also allows for the estimation of complex models involving multiple latent variables and observed indicators.
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Please make SEM with Likert based data.
Using semplot, what does those codes represent on the path diagram?
Very helpful for understanding SEM in R
Thank you
Can i use it also if one of my dependent variable is dummy?
Yes, you can use even if one of your dependent variables is a dummy variable (binary). SEM can handle both continuous and categorical (including binary) variables.
I shall soon upload one more video tutorial on SEM using likert scale data.
@@AGRONInfoTech does this specification consider the correlation between errors? For instance in stata to get estimation coefficient equivalent to ivregress you must specify cov(e*e), is it the same in this package?
@@chiaras2274 In the lavaan package for R, you can specify correlations between the errors of different equations (residual covariances) directly in the model syntax. This is similar to specifying cov(e*e) in Stata to account for Correlationterms.
For example:
# Define the model with correlation term
model
can you provide the dataset file.
You can download the dataset from the link provided in the description of this video.
How to rename the text in boxes on SEM plot?
You can achieve this while specifying the model and creating the mod.id object. Simply use the desired names for the latent variables instead of "EA" and "YC." For other variables used from the dataset, you can rename them either in the Excel sheet before importing the data or by defining the column names after importing it.
Sir, I have analysed 7 fractions of soil zinc and other soil chemical properties. How can I develop a SEM using my data. Could you please teach me.
You may use the following model for your data as I am not aware of the complete list of variables. Here is the model:
# Example SEM model
model
@@AGRONInfoTech Thank you Sir
@ldsharma6546 you are welcome
hii, what journal do you get the data in the video from?
Hi it's not published data. I have used it just as an example. You may say it's dummy dataset
How is lavaan different from other model-generating packages in R?
Lavaan supports a wide range of models, including confirmatory factor analysis (CFA), path analysis, structural equation modeling, and growth curve modeling. It also allows for the estimation of complex models involving multiple latent variables and observed indicators.
@@AGRONInfoTech thanks.
can we use Pls method ?
Yes, absolutely! Partial Least Squares (PLS) is a popular method for structural equation modeling (SEM) and can be effectively used.
good job, I need codes to use the model. Anyone should help me
Thanks. The link is given in the description of this video. My website is under renewal process and will work within 24 hours