Structural equation modeling (SEM) is an analytical approach for testing a priori hypothesis on causal relationships among variables of interest. For doing the computational aspect of SEM, software packages such as AMOS, EQS, R lavaan, LISREL, or Mplus can be utilized. Since you are seeking a free SEM software, the lavaan package for R could be the one you go for. Here are some relevantly interesting reads.
Andersen, H. K. (2021). A closer look at random and fixed effects panel regression in structural equation modeling using lavaan. Structural Equation Modeling: A Multidisciplinary Journal, 0(0), 1–11. https://doi.org/10.1080/10705511.2021.1963255
Keith, T. Z. (2019). Multiple regression and beyond: An introduction to multiple regression and structural equation modeling (3rd ed.). Routledge. https://doi.org/10.4324/9781315162348
Mair, P. (2018). Modern psychometrics with R. Springer. https://doi.org/10.1007/978-3-319-93177-7
Tarka, P. (2018). An overview of structural equation modeling: Its beginnings, historical development, usefulness and controversies in the social sciences. Quality & Quantity, 52(1), 313–354. https://doi.org/10.1007/s11135-017-0469-8
Wang, Y. A., & Rhemtulla, M. (2021). Power analysis for parameter estimation in structural equation modeling: A discussion and tutorial. Advances in Methods and Practices in Psychological Science, 4(1), 2515245920918253. https://doi.org/10.1177/2515245920918253