Respondent driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations (e.g. drug users, men who have sex with men, people with HIV). Similar to snowball sampling, initial seed respondents recruit additional respondents from their network of friends....

In this paper, we develop a new model-based method to inference on totals and averages of nite populations segmented in planned domains or strata. Within each stratum, we decompose the total as the sum of its sampled and unsampled parts, making inference on the unsampled part using Bayesian...

Respondent driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations (e.g. drug users, men who have sex with men, people with HIV). Similar to snowball sampling, initial seed respondents recruit additional respondents from their network of friends....

Respondent driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations (e.g. drug users, men who have sex with men, people with HIV). Similar to snowball sampling, initial seed respondents recruit additional respondents from their network of friends....

While permutation tests and bootstraps have very wide-ranging application, both share a common potential drawback: as data-intensive resampling methods, both can be runtime prohibitive when applied to large or even medium-sized data samples drawn from large datasets. The data explosion over the...

Six permutation test algorithms coded in SAS® are compared. The fastest (“OPDN”), which uses no modules beyond Base SAS®, achieves speed increases orders of magnitude faster than the relevant “built-in” SAS® procedures (over 215x faster than Proc SurveySelect, over 350x faster than...

This article has provided a critical review of sampling procedures in the context of Sierra Leone. The basics of the two major types of sampling procedures (probability and non-probability) have been explained, with a view of shedding light on their usage to assist researchers in their pursuance...

Researchers frequently test and improve model fit by holding a sample constant and varying the model. We propose methods to test and improve sample fit by holding a model constant and varying the sample. Much as the bootstrap is a well-known method to re-sample data and estimate the uncertainty...

The paper studies the impact of the sampling frequency on the volatility of financial time series. We suggest to model the dependence of volatility on sampling frequency via delay equations for the underlying prices. It appears that these equations allow to model the price processes with...

Unit nonresponse or attrition in panel data sets is often a source of nonrandom measurement error. Why certain individuals attrite from longitudinal studies and how to minimize this phenomenon have been examined by researchers. However, this research has typically focused on data sets collected...