Krahasoni metodat
Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.
| Kampionim Adativ me Kuota× | Kampioni i shtresuar× | |
|---|---|---|
| Fusha | Metodologjia e anketave | Metodologjia e anketave |
| Familja | Process / pipeline | Process / pipeline |
| Viti i origjinës≠ | 2000s (adaptive extension of quota principles) | 1977 |
| Krijuesi≠ | Grounded in quota sampling (Quota sampling formalized early 20th century); adaptive extensions developed within responsive survey design frameworks (Groves & Heeringa, 2006) | William G. Cochran |
| Lloji≠ | Non-probability sampling with adaptive control | Probability-based survey sampling design |
| Burimi themelues≠ | Groves, R. M., & Heeringa, S. G. (2006). Responsive design for household surveys: Tools for actively controlling survey errors and costs. Journal of the Royal Statistical Society: Series A, 169(3), 439–457. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7 |
| Emërtime të tjera≠ | responsive quota sampling, dynamic quota sampling, iterative quota sampling | Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme |
| Të lidhura≠ | 3 | 2 |
| Përmbledhja≠ | Adaptive quota sampling is a non-probability sampling approach that starts with predefined demographic or characteristic-based quotas and then adjusts those quotas during data collection in response to emerging response patterns, nonresponse trends, or representativeness concerns. By treating the sampling process as iterative rather than fixed, it allows researchers to correct imbalances in real time and improve the final sample composition without restarting data collection from scratch. | Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics. |
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