Balancing Efficiency and Feasibility: A Sensitivity Analysis of the Augmentation Parameter in the Finite Selection Model
Fuente:
arXiv
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2026
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866917318878035968 |
|---|---|
| author | Kadhem, Safaa K. |
| author_facet | Kadhem, Safaa K. |
| contents | This paper investigates the role of the augmentation parameter in the Finite Selection Model (FSM) and its impact on estimator performance. Through a comprehensive Monte Carlo simulation study, we analyze the sensitivity of bias, variance, and mean squared error to different values of the augmentation parameter. The results demonstrate that moderate augmentation improves covariate balance while maintaining estimation efficiency. However, excessive augmentation may increase variance and reduce estimator stability. The findings provide practical guidelines for selecting the augmentation parameter in applied experimental design settings. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_06493 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Balancing Efficiency and Feasibility: A Sensitivity Analysis of the Augmentation Parameter in the Finite Selection Model Kadhem, Safaa K. Methodology This paper investigates the role of the augmentation parameter in the Finite Selection Model (FSM) and its impact on estimator performance. Through a comprehensive Monte Carlo simulation study, we analyze the sensitivity of bias, variance, and mean squared error to different values of the augmentation parameter. The results demonstrate that moderate augmentation improves covariate balance while maintaining estimation efficiency. However, excessive augmentation may increase variance and reduce estimator stability. The findings provide practical guidelines for selecting the augmentation parameter in applied experimental design settings. |
| title | Balancing Efficiency and Feasibility: A Sensitivity Analysis of the Augmentation Parameter in the Finite Selection Model |
| topic | Methodology |
| url | https://arxiv.org/abs/2603.06493 |