Harvard Case Study

MSG continually tries to build bridges to the academic and social science world by using long established contacts coupled with the will, desire and need to use its assets to assist in projects that serve the public good.  Frequently these projects involve project consultation, pro bona delivery of sample frame design and data or, as was the case with an MSG/Harvard University project a combination of all three.

In the Fall of 2014, the student’s in Professor Chase Harrison’s GVT 1010 Undergraduate Survey Research class undertook a multi-mode project to gauge the urban/suburban attitudes of residents in the Boston area.  MSG supplied not only the ABS sample but also allowed the students to consult with MSG personnel.  The result was a high response rate and statistically sound survey finding.  MSG would like to let all of academia know that we are available to work on select projects and can offer advice, suggestions and data if the project meets qualifications.

As Professor Harrison commented “MSG’s willingness to donate the sample for this project is just incredible.  I always encourage my students to use the best tools available, although I don’t always have the resources to help them use those tools, especially for things like general-population samples.  Thanks to MSG, this group was able to use a sample that otherwise would have been beyond their reach, and were able to experience what it is like to work on real-time survey with professional tools.”

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Split-Frame Sampling

Oftentimes, researchers are faced with the challenging task of targeting rare domains in a population while maintaining the probability-based nature of the employed sample.  For instance, in a national RDD sample it might be necessary to oversample households with small children or those with even less prevalent attributes.  While an epsem sampling design, whereby all numbers have the same chance of selection, will provide the most efficient sample with respect to the precision of survey estimates, from a cost perspective such a design can be completely prohibitive due to the required level of screening for reaching eligible households.  This is where a cleverly designed stratified sampling alternative that employs disproportional allocation can prove highly valuable.

In practice, an optimal sample allocation scheme takes into account the unit cost per interview in each sampling stratum.  As such, a stratum with a high incidence of reaching members of the target population will receive a higher allocation as compared to other strata.  This disproportionate sample allocation should be exercised while providing a non-zero chance of selection for all telephone numbers to ensure a probability-based sample.

The objective of this stratification is to provide a means for over sampling the target populations by segregating higher incidence households into distinct sampling strata.  This is done by matching all numbers against commercial databases, which contain household and individual level demographic data, and identifying the numbers that meet the specified target.

With access to all the top commercial databases Marketing Systems Group can provide cost-effective solutions for sample surveys that aim to target rare domains.  By placing such telephone numbers in the “top” or high incidence stratum and the remaining telephone numbers covering the geography of interest in another, you can create a complete sampling frame.  Subsequently, using an optimization procedure a higher sampling fraction will be determined for the top stratum cognizant of the design effect that will result from a disproportional sample allocation and will need to be adjusted for when weighting.