방법 비교

	Time-Location Sampling	Network Scale-Up Method
분야	Migration Studies	Migration Studies
계열	Process / pipeline	Process / pipeline
기원 연도	2001	1998
창시자	CDC Community Intervention Trial for Youth study team (Muhib, Stueve, and colleagues)	Peter Killworth, Christopher McCarty, H. Russell Bernard, and colleagues
유형	Probability-sampling pipeline for hard-to-reach mobile populations	Indirect network-based size-estimation pipeline for hidden populations
원전	Muhib, F. B., Lin, L. S., Stueve, A., Miller, R. L., Ford, W. L., Johnson, W. D., & Smith, P. J. (2001). A Venue-Based Method for Sampling Hard-to-Reach Populations. Public Health Reports, 116(Suppl 1), 216-222.	Bernard, H. R., Hallett, T., Iovita, A., Johnsen, E. C., Lyerla, R., McCarty, C., Mahy, M., Salganik, M. J., & Stroup, S. (2010). Counting Hard-to-Count Populations: The Network Scale-Up Method for Public Health. Sexually Transmitted Infections, 86(Suppl 2), ii11-ii15.
별칭	Venue-Based Sampling, Time-Space Sampling, Venue-Day-Time Sampling, VDTS	NSUM, Scale-Up Method, Aggregate Relational Data Method, Known-Population Network Estimation
관련	3	3
요약	Time-location sampling, also called venue-based or venue-day-time sampling, is a probability-sampling method for reaching populations that lack any list frame but reliably congregate at identifiable places and times. Developed and codified by Muhib, Stueve, and colleagues in a 2001 Public Health Reports article for a CDC youth study, it replaces the impossible task of enumerating a hidden population with the tractable task of enumerating the venues, days, and time slots where that population gathers. The analyst first builds an ethnographic frame of venue-day-time (VDT) units, then draws units at random, intercepts and enrolls eligible attendees on site, and finally weights respondents by how often they attend so that frequent venue-goers do not dominate the estimate. Because selection probabilities are known at each stage, the design yields defensible, variance-estimable population quantities rather than a convenience sample. For migration research it is especially valuable: day laborers at hiring corners, migrants at remittance shops, consulates, places of worship, markets, and transit hubs are mobile and unlisted, but they are observable in space and time. The method thus converts the visibility of a mobile migrant population into a genuine sampling frame.	The network scale-up method (NSUM) estimates the size of a hidden population — such as undocumented migrants or members of a stigmatized group — by asking ordinary people in a general survey how many members of that population they personally know. Developed by Killworth, McCarty, Bernard, and colleagues and formalized in their 1998 Evaluation Review paper, it rests on a simple bookkeeping idea: if you know roughly how many people each respondent knows in total, and you observe how many of those acquaintances belong to the hidden group, you can scale that fraction up to the whole society. The trick to recovering the total acquaintance count is to ask about several groups whose sizes are already known — people named Michael, nurses, women who gave birth last year — and use the responses to calibrate each respondent's personal-network size. Bernard and colleagues' 2010 review brought the method into mainstream public-health surveillance and emphasized two crucial corrections: transmission bias, because people often do not know which of their acquaintances belong to a hidden group, and barrier effects, because the hidden group may be socially clustered away from typical respondents. For migration research NSUM is attractive precisely because it never requires contacting migrants directly; it infers their numbers from the social fabric of the wider population.