SaNaPLS takes you from an uploaded survey file to latent variable scores, bootstrapped path coefficients, fsQCA configurations, neural-network importance rankings and cIPMA — with every cut-off traced to a published source. Nothing you upload ever leaves your browser.
PLS-SEM path model, reliability and validity
Configurations for high and low outcomes
What matters most, and what's necessary
Why not just use what you have
Runs in any modern browser — Windows, Mac or Linux, no setup.
Every calculation runs on your machine. Nothing is uploaded to a server.
After the first visit, keep running analyses without a connection.
Upload once; every tool below reads the same file and the same constructs.
The workflow
Bring in a CSV, Excel or SPSS file, confirm what each column is, and screen the data once.
Summarise your sample, cross-tabulate demographics, and check every item and score for normality.
Calculate latent variable scores with PLS-SEM, then check reliability, validity and path significance with bootstrapping.
Go beyond the path model: fsQCA configurations, neural-network importance rankings, and cIPMA — built on your estimated model or uploaded scores.
No guessing at thresholds
Developed by
Professor in Management and IT
Department of Management and Marketing