WHY SMARTPLS?
PETUA PASCASISWAZAH
03/12/2018
- PLS makes fewer demands regarding sample size than other methods
- PLS does not require normal-distributed input data. Normal distributions are usually desirable, especially when working with CB-SEM. In contrast, PLS-SEM generally makes no assumptions about data distributions
- PLS can be applied to complex structural equation models with a large number of constructs.
- PLS is able to handle both reflective and formative constructs.
- PLS is better suited for theory development than for theory
testing. - PLS is especially useful for prediction.
KOMEN ANDA
