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AN EMPIRICAL TEST OF RESPONDENT-DRIVEN SAMPLING: POINT ESTIMATES, VARIANCE, DEGREE MEASURES, AND OUT-OF-EQUILIBRIUM DATA
population RESPONDENT-DRIVEN SAMPLING
2015/9/11
This paper, which is the first large scale application of Respondent-Driven
Sampling (RDS) to non-hidden populations, tests three factors related to RDS estimation
against institutional data using...
Sampling international migrants with origin-based snowballing method: New evidence on biases and limitations
Sampling international migrants limitations
2014/11/20
This paper provides a methodological assessment of the advantages and drawbacks of
the origin-based snowballing technique as a reliable method to construct representative
samples of international ...
Sampling and Surveying Hard-to-Reach Populations for Demographic Research: A Study of Female Labor Migrants in Moscow, Russia
Central Asia migration Russia sampling survey methodology
2014/11/20
Because household-based survey designs are notoriously ineffective in studying hard-to-reach groups such as irregular migrants, these groups, however numerically large they may be, are rarely represen...
Estimating the Size of the Methamphetamine-Using Population in New York City Using Network Sampling Techniques
Population Estimation Network Methods Methamphetamine Anonymous Sampling
2013/1/31
As part of a recent study of the dynamics of the retail market for methamphetamine use in New York City, we used network sampling methods to estimate the size of the total networked population. This p...
The Timing of Earnings Sampling over the Life-Cycle and IV Identification of the Return to Schooling
returns to schooling instrumental variable methods dynamic discrete choice dynamic programming
2012/10/23
We show that within a life-cycle skill accumulation model, IV identification of the return to schooling parameter is either achieved at any point in the life-cycle where the level of skills accumulate...
Model-based seasonally adjusted estimates and sampling error
seasonally adjusted estimates sampling error
2009/3/31
Estimating certain CPS series with a model that filters out sampling error
may reduce volatility in the time series, facilitating more meaningful trend analysis.