Testing the Psychometric Properties and Equivalence of the Czech Version of the Satisfaction with Life Scale (SWLS) using Confirmatory Factor Analysis, Item Response Theory, and Bayesian Modelling
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Bibliographic record
Abstract
Testing the Psychometric Properties and Equivalence of the Czech Version of the Satisfaction with Life Scale (SWLS) using Confirmatory Factor Analysis, Item Response Theory, and Bayesian ModellingThe Satisfaction with Life Scale (SWLS) is one of the most commonly used instruments for measuring life satisfaction.The aim of this study is to test the psychometric properties of the Czech version of the SWLS using Confirmatory Factor Analysis (CFA) and Item Response Theory (IRT) and to test its invariance between social groups in terms of gender, age, and education using Bayesian modelling on a representative sample of the Czech online population, as the scalehas not yet been tested on representative data in the Czech Republic.The research sample consists of 960 respondents aged 18 to 69 years.The results confirmed that the psychometric properties of the Czech version of the SWLS are very good, but, at the same time, it is evident that the fifth item shows worse results than the other four items.In terms of dimensionality, CFA and IRT confirmed its modified singlefactor structure with correlated residuals between the fourth and fifth items as the most appropriate.Testing for approximate measurement invariance using Bayesian modelling showed that the SWLS measures comparably between groups based on gender, age, and education.In conclusion, the Czech version of the SWLS is a suitable, verified, and reliable instrument for measuring the life satisfaction of Czech citizens.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it