you should run appropriate regression according to data type of your dependent variable.In general situation you can use t-test to test the significant of individual regression if simple or multiple regression applicable and F- test for significance of complete regression in multiple regression situation. There are many test which are applicable on you data-set according to your objective.
I think you need to carry out some sort of statistical analysis to screen the independent variables that have meaningful (significant) association to the dependent variable. For this you can use either chi-square test or ANOVA depending on the nature of your data. Then you can choose either interval or mean reports. That is all I can say from the information you provided. I hope this helps.
In general terms, it depends on the purpose of the work. At first, some questions should be answered. For example, if there is someting in mind, are the necessary assumptions fulfilled to proceed further? In case of problem, are there alternatives?
Regards
In case of indicators and latent variables you can use either common factor analysis (SEM) for reflective model or for informative model, principle components analysis ( PLS-SEM)
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