Hi, I am analyzing the data of this questionnaire (link below). Most of dependent variables are dichotomous/binary and independent variables are ordinal (educational level), scale (age) and binary (gender).
I know I could use a logistic regression, for example to predict the effect of independent variable on a binary response variable like "I use a tablet computer".
But I would like to create a model of latent variables (so first I need some factors), created from dependent variables, that would show something similar as a Structural equation model. For example that latent variables created from items like different internet usage, different skills and different options of internet availability (exogenous) explain about xx percent of the variance of the latent variable created from items describing e-government use (endogenous).
But maybe I am mixing apples and oranges :-)
Thank you for any suggestions
(I use SPSS and AMOS, also heard about the FACTOR software)
https://circabc.europa.eu/sd/a/b4f20040-f950-496b-8ab9-89398bf82f01/Questionnaire%20HH%202016%20v%203.2.pdf
http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470971924.html provide details of how latent variable models can be used with different measurement levels for the observed and latent variables. It sounds like your first task is turning a series of binary observed variables into a smaller number of latent variables. This is covered in their book, and the label for these models when the latent variables are assumed continuous is latent trait models. In education research they are often called item response models (or item response theory, though most in education who even use the word theory here are not invested in this statistical model being an accurate model of how students answer questions).
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