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BigSEM can be used either locally as R packages or online using our web app. R Package We have two R packages in the development stage that can now be installed from GitHub. We plan to upload the packages to CRAN before the end of December, 2024. The R packa...

One can conduct the analysis by drawing a path diagram. To start, click the "Path Diagram" button. The interface below will appear: A path diagram can be drawn through the buttons in the interface. In the example, we have a mediation model where the text is...

Sentiment analysis is the process of systematically identifying and quantifying the sentiment expressed in a text. Lexicon-based / dictionary-based approach A common method is the lexicon-based approach, where each word is assigned a sentiment score, and the...

Embedding techniques are widely used in modern NLP. These methods transform text into numerical vectors, capturing both semantic and syntactic relationships with high fidelity (Patil et al., 2023). Conceptually, this process can be viewed as factor analysis or...

Network data can be integrated into the SEM framework in different ways. We focus on two main approaches here. The first approach extracts the information from a network based on each participant and then use that information as variable(s) in a SEM model. In ...

The function sem.net can be used to fit a SEM model with network data using node statistics as variables. User-specified network statistics will be calculated and used as variables instead of the networks themselves in the SEM. The following choices of networ...

We will use several datasets to illustrate the use of our software. Friendship Network Data In this dataset, information on friendship network, alcohol use, smoking, the big five personality traits, and academic performance among college students is collecte...

The node-based latent space model approach calculates latent positions of the networks, and use them in the SEM analysis along with non-network variables. Simulated Data Example To begin with, a random simulated dataset can be used to demonstrate the usage o...

The edge based analysis can be conducted using the function sem.net.edge. The idea behind this method is that the edge values can be the unit of analysis if we transform non-network covariates into pair-based values.  Simulated Data Example To begin with, a ...

The R function sem.net.edge.lsm can be used to conduct edge based analysis with latent space model. In this case, the latent distance between each pair of individuals is used along with the transformed non-network covariates in SEM. Simulated Data Example To...

The network data analysis can also be conducted using our online app available at: https://bigsem.psychstat.org/app . To use the app, one need to register as a user to protect the data of the users. Once logging in, a user with work with an interface like belo...

For illustration, we use a set of student evaluation of teaching data. The data were scraped from an online website conforming to its site requirement, containing 38,240 teaching evaluations on 1,000 instructors.  For each evaluation, we have information on t...

The R package TextSEM can be used for SEM analysis with text data. To install the package, please use ## Install the package for text analysis remotes::install_github("Stan7s/TextSEM") ## The package can be installed from CRAN directly in the future # in...

Here we show how to conduct different types of analysis. Mediation analysis with dictionary-based sentiment The model used here is  The video tutorial Mediation analysis with AI-based sentiment The model is  Factor analysis In this example, ...