metis User Guide

1. What is metis?

metis is a free desktop app for students, lecturers, and researchers who use Partial Least Squares Structural Equation Modelling (PLS-SEM). It brings the main parts of a study into one place: create a workspace, add your data, draw your model, run the analysis, and review the results without writing R code.

R and seminr do the statistical calculations in the background. You work with a visual interface, so you can focus on your research question instead of scripts, setup files, and folder juggling.

Tark is the reporting helper inside metis. Once a model has saved results, Tark collects the key tables and an optional path diagram into a preview you can copy into Word, a thesis draft, or a paper.

2. Computer Requirements

metis is currently available for Windows and macOS. The setup below is a good starting point:

3. Choosing Your Installer

metis comes in two installers. Both give you the same app. The difference is whether metis brings the R support it needs or uses the R setup already on your computer. Downloads are direct from the release page; no form is required.

3.2 Bundle or Lite?

4. First Launch

The first launch is a short setup check. Bundle users should be ready after the included calculation tools are prepared. Lite users will see metis look for R and check the packages needed for analysis.

5. Getting Started

5.1 Application Overview

When metis opens, you start on Workspace Home. Think of a workspace as a study folder. It can hold datasets, models, and saved results, so the pieces of one project stay together.

You can create a new workspace, open an existing one, pin important workspaces, switch between grid and list view, and reopen recent models from the title bar. A model opens on the canvas, where you can work with multiple model tabs in the same session.

5.2 Importing Your Data

1. Choose Import Dataset from the workspace or canvas.
2. Select a CSV or Excel file. For CSV files, metis lets you confirm how the file is separated and saved.
3. Review the preview, missing-value count, and detected variables.
4. Open the dataset view if you need to clean small issues before modelling.

5.3 Reviewing and Cleaning Data

The dataset view is for quick, practical cleanup. You can rename columns, edit cells, delete rows or columns, add simple calculated columns such as mean or sum, and save the cleaned data back to the workspace.

A workspace can hold up to three datasets. From the Dataset Manager, choose which dataset a model should use, rename datasets, remove older versions, or add a new dataset when you need to compare versions.

5.4 Building Your Model

• Add constructs, which are the ideas or concepts you want to study.
• Drag dataset variables onto each construct as indicators, such as survey items or measures.
• Choose whether each construct is reflective or formative.
• Move indicators around the construct so the diagram stays readable.
• Draw arrows between constructs to show which ideas you expect to influence others. You can also connect a construct to an existing arrow when you need a moderation relationship.
• Use tabs to keep more than one model open, and save manually whenever you want to lock in the latest version.

5.5 Running the Analysis

1. Click the calculate button on the canvas to run PLS-SEM.
2. Confirm the algorithm settings. The defaults are a good starting point for most models.
3. metis checks that your model has the needed pieces and that the dataset columns match before running.
4. When the run finishes, results open automatically and can be saved to the workspace.

6. Reading Results

The Results View keeps each analysis mode in its own clear view: PLS-SEM, Bootstrap, PLSpredict, and Advanced analysis. The left side lists the result groups, while the main area shows the selected table, chart, or path diagram.

Some panels include a chart above the table. You can copy visible tables, download tables for Excel, export a full HTML report, or copy the R script used to reproduce the model.

7. Bootstrap

Bootstrapping repeats the analysis many times with repeated samples from your data. This helps you judge whether paths and measurement results are stable enough to report. metis lets you choose the number of repeated samples and the confidence settings before the run starts.

1. From the Model Canvas, choose Analysis > Run Bootstrap.
2. Review the default settings. The current default is 500 repeated samples.
3. Run Bootstrap and wait for the results to open.
4. Save the results if you want to reopen them later or use them in Tark.

8. PLSpredict

PLSpredict checks how well your model predicts data it has not already fitted. You can choose the number of folds and repetitions, and you can turn on CVPAT when you want the extra prediction test.

1. Select Analysis > PLSpredict from the menu bar.
2. Set folds and repetitions. metis also shows how many prediction checks will run.
3. Turn on CVPAT if you want that summary included.
4. Review Q²predict, PLS vs LM comparison, prediction errors, and the histogram panels in the results view.

9. Advanced Analysis

Advanced analysis becomes available after you run PLS-SEM for the current model. It is meant for follow-up interpretation, especially when you want to understand which constructs deserve attention for a chosen target outcome.

1. Run and save a PLS-SEM result for the model.
2. Choose Analysis > Advanced analysis.
3. Select a target construct and choose whether to include only direct influences or earlier influences too.
4. Select IPMA, NCA, cIPMA, or keep all three selected.
5. Run the analysis and review the priority map, construct table, necessity check, bottleneck table, and cIPMA priorities.

10. Tark Reports

Tark is the report helper inside metis. It takes saved results from a model and turns them into clean tables for writing. The goal is not to replace your interpretation, but to remove the busy work of collecting results, aligning labels, and rebuilding tables by hand.

What Tark creates

• Measurement model tables with indicator quality, reliability, validity, and VIF where available.
• Discriminant validity tables.
• Structural model tables for hypothesis testing, confidence intervals, effect sizes, and decisions.
• Explanatory and predictive power tables.
• Model fit tables.
• Optional PLSpredict and advanced-analysis tables when those saved results are included.
• An optional path diagram with the values you choose to show.

How to use Tark

1. Run and save PLS-SEM, Bootstrap, and PLSpredict for the model you want to report.
2. Click Tark it in the title bar.
3. Choose the workspace and model. If a model is not ready, metis tells you which saved result is missing.
4. Add a report title, choose full construct names or abbreviations, and decide whether to include the path diagram.
5. Preview the report tables, then copy one table or copy everything into Word.

11. Exporting Results

12. Data Privacy & Security

metis is built for research data that should stay close to you. Your workspace, dataset, model, and results are stored on your computer.

13. Known Limitations, v0.2.1

• Windows and macOS releases. Linux, Android, iOS, and web versions are not available in this release.
• CSV and Excel are the supported import formats. Other data formats may appear in the file picker, but use CSV or Excel for the smoothest experience.
• Tark prepares tables, not the written argument. It gives you cleaner tables and diagrams, but you still write the interpretation for your study.
• Large calculations can take time. metis runs Bootstrap, PLSpredict, and advanced analysis on your computer through R and seminr. Large models, 5,000-10,000 bootstrap samples, other work running on your computer, and older hardware can make calculations take several minutes. A longer run does not mean the calculation has failed; metis keeps working locally until the result is ready.
• Saved results matter. Tark and later review tools work best when you save PLS-SEM, Bootstrap, PLSpredict, and any Advanced analysis results you want to reuse.

Licence & Support