How to Use Package "simsem" for Sample Size Determination in SEM: Validation Project?


In my project, I am working on a CFA SEM-based model for validation analysis to adopt a questionnaire translation to the native language in my country.

Due to certain constraints, I am only able to use purposive sampling (e.g. only psychology undergraduates students are sampled due to the narrow nature of the questionnaire; it asks participants specifically to provide a likert-scale points to one's own major under the observed variables).

I have 3 questions:
I am curious if the package "simsem" takes into account of non-random sampling method? In other words, does the package only applies to random sampling?

To provide context:

My model is a latent model; 3 Latent Variables, 3 Indicators for two Latent Variables and the last Latent Variable with 4 indicators.

Hence, Total of 3 Latent and 10 Measured Variables.

Paramaratization nature of CFA model:

Two latent variables are correlated with each other, while the same last latent variable is negatively correlated both of the other two.

All indicator / measured variables are expected to positively estimate unto their respective latent variables.

As an amateur, how to I determine / interpret / visualize relevant indices that will judge an appropriate sample size?

What does it mean when (
(need to be SimMatrix object). [in terms of writing the coding]

  • LX or LY for factor loading matrix (need to be SimMatrix object).

I never use R, but I am willing to learn through the coding. They seems okay but of course not so for a first-timer. It feels so close to finding the right spot but I am not there yet.

For clarifications on my research model, you may refer to this site:'s_Guide_for_the_Expectancy-Value-Cost_Survey_of_Student_Motivation

I also found a lot of resources to look at, but I am not sure which is appropriate for my project inquiry:

This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.