QuickPLS Pro practice data
Use a higher-order control system as a mediator
Invented indicators for a focused higher-order mediation teaching model.
One row: one fictional manufacturing business. Rows: 230.
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What is in the file?
Assessment columns contain continuous teaching scores between 1 and 7. A higher score means more of the property named in the table. Any binary assignment uses 0 and 1 as labels, as defined below. These are not real questionnaire responses or observations from the cited paper. The file contains no missing values. Keep case_id for checking rows, and leave it out of the analysis.
| Column | Meaning | Role | Values |
|---|---|---|---|
| case_id | Fictional case identifier | Identifier; exclude from analysis | Unique text label |
| RESPONS1 | Responsible-business commitment, practice item 1 | predictor | Continuous teaching score, 1 to 7; higher means more of the named property |
| RESPONS2 | Responsible-business commitment, practice item 2 | predictor | Continuous teaching score, 1 to 7; higher means more of the named property |
| RESPONS3 | Responsible-business commitment, practice item 3 | predictor | Continuous teaching score, 1 to 7; higher means more of the named property |
| GOALS1 | Sustainability objectives, practice item 1 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| GOALS2 | Sustainability objectives, practice item 2 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| GOALS3 | Sustainability objectives, practice item 3 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| MONITOR1 | Monitoring routines, practice item 1 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| MONITOR2 | Monitoring routines, practice item 2 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| MONITOR3 | Monitoring routines, practice item 3 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| LEARN1 | Learning routines, practice item 1 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| LEARN2 | Learning routines, practice item 2 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| LEARN3 | Learning routines, practice item 3 | dimension | Continuous teaching score, 1 to 7; higher means more of the named property |
| RESIL1 | Organisational resilience, practice item 1 | outcome | Continuous teaching score, 1 to 7; higher means more of the named property |
| RESIL2 | Organisational resilience, practice item 2 | outcome | Continuous teaching score, 1 to 7; higher means more of the named property |
| RESIL3 | Organisational resilience, practice item 3 | outcome | Continuous teaching score, 1 to 7; higher means more of the named property |
Before you run the analysis
Import the CSV, check the row count and column types, then follow the model or calibration choices in the tutorial. Similar-looking columns are not automatically interchangeable. Do not use these data to support a claim about real people, organisations or the paper's findings.
Keep this column guide beside the lesson. Match the variable names and score directions before interpreting a result.
How the example was made
This file was generated from a saved random seed (71013) and an original teaching design. Each factor has its own random variation; some include planned relationships so you can practise the method. Item columns add separate measurement noise. The data are scaled and bounded before export, so generation coefficients are not expected fitted coefficients. No QuickPLS result values are asserted by this codebook.
The sample size serves the exercise. Plan the sample size for a real study separately. Group labels, where present, are assigned independently and do not establish real group differences.
The original practice data are released under CC0 1.0. The source paper remains the work of its authors and publisher.
File identity
SHA-256: 8bac47c2efac6cc00f5e8d3aac83b67bf4aa1727fbb014c77fbe6db4e38c5a65