Factor analysis, in which both latent (unobserved) and manifest (observed) variables are continuous, is perhaps the best known.
In latent profile analysis the latent variable (e.g. consumer segments) is categorical and the manifest variables (e.g. responses to rating scales) are continuous.
Latent trait models (e.g. item response theory) are characterized by continuous latent variables and categorical manifest variables (e.g. correct or incorrect answers to test items).
In latent class analysis both latent and observed variables are categorical.
There are also hybrid models which include both continuous and categorical latent and manifest variables.
In some models there is a distinction between dependent and independent variables. Censored, truncated and count variables can also be accommodated.
Any of these models can be multilevel (hierarchical) or longitudinal and can incorporate exogenous variables (covariates).
This popular book is focused on latent class analysis and its longitudinal extension, latent transition analysis. It is well written and covers theoretical and technical issues as well as application.
Factor analysis, in which both latent (unobserved) and manifest (observed) variables are continuous, is perhaps the best known.
In latent profile analysis the latent variable (e.g. consumer segments) is categorical and the manifest variables (e.g. responses to rating scales) are continuous.
Latent trait models (e.g. item response theory) are characterized by continuous latent variables and categorical manifest variables (e.g. correct or incorrect answers to test items).
In latent class analysis both latent and observed variables are categorical.
There are also hybrid models which include both continuous and categorical latent and manifest variables.
In some models there is a distinction between dependent and independent variables. Censored, truncated and count variables can also be accommodated.
Any of these models can be multilevel (hierarchical) or longitudinal and can incorporate exogenous variables (covariates).
This popular book is focused on latent class analysis and its longitudinal extension, latent transition analysis. It is well written and covers theoretical and technical issues as well as application.
From the Files app, scroll down to Internal storage, and tap on WhatsApp. Once you’re there, go to Media and then WhatsApp Stickers. Don’t be surprised if you find a large number of files in that folder—it holds your personal collection of stickers and every one you’ve ever received. Even the bad ones.Tap the three dots in the top right corner of your screen to Select all. If you want to trim the fat and grab only the best of the best, this is the perfect time to do so: choose the ones you want to export by long-pressing one file to activate selection mode, and then tapping on the rest. Once you’re done, hit the Share button (that “less than”-like symbol at the top of your screen). If you have a big collection—more than 500 stickers, for example—it’s possible that nothing will happen when you tap the Share button. Be patient—your phone’s just struggling with a heavy load.On the menu that pops from the bottom of the screen, choose Telegram, and then select the chat named Saved messages. This is a chat only you can see, and it will serve as your sticker bank. Unlike WhatsApp, Telegram doesn’t store your favorite stickers in a quick-access reservoir right beside the typing field, but you’ll be able to snatch them out of your Saved messages chat and forward them to any of your Telegram contacts. This also means you won’t have a quick way to save incoming stickers like you did on WhatsApp, so you’ll have to forward them from one chat to the other.
