Purposive Sampling in the Analysis of Count Data

Year: 2016       Vol.: 65       No.: 1      

Authors: Paolo Victor T. Redondo

Abstract:

Purposive sampling is a non-probability sampling method which is oftentimes used whenever random/probability sampling is not efficient, too costly (either in finance or time) and not feasible. Also, most of the data collected for studies in the present time exhibit the property of count and thus, analysis of such data needs the appropriate tool; commonly the Poisson Regression. The goal of this study is to determine whether the relative location-based purposive sampling can improve the estimates produced by the Poisson regression and if the proposed sampling procedure can reduce the required sample size to have a more efficient and good quality results simultaneously. Simulation of different scenarios are done and several possible partitions (based on relative location) from where the sample will come from are considered. Some partitions are deemed to work better even for small sample size, say 50, while others work as good as their respective simple random sample counterparts.

Keywords: purposive sampling, poisson regression, sample size

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