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Member Training: A Quick Introduction to Weighting in Complex Samples

by guest contributer 1 Comment

A few years back the winning t-shirt design in a contest for the American Association of Public Opinion Research read “Weighting is the Hardest Part.” And I don’t think the t-shirt was referring to anything about patience!

Most statistical methods assume that every individual in the sample has the same chance of selection.

Complex Sample Surveys are different. They use multistage sampling designs that include stratification and cluster sampling. As a result, the assumption that every selected unit has the same chance of selection is not true.

To get statistical estimates that accurately reflect the population, cases in these samples need to be weighted. If not, all statistical estimates and their standard errors will be biased.

But selection probabilities are only part of weighting. Other common survey issues can also be accounted for by weighting. These include non-sampling error, coverage, and non-response.

In this introductory webinar, we will give you an overview of weighting for data from complex sample designs. We will highlight various adjustments that can be included in creating final sampling weights.

We’ll also discuss some modern methods for variance estimation with sampling weights, including replicate weights.

We’ll end with a high-level discussion of using survey weights in your statistical analysis.

By the end of this webinar, you’ll have a better understanding of how to approach using weights in your own statistical analysis.


Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.

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About the Instructor

Trent D. Buskirk, PhD, received his PhD in Statistics from Arizona State University with an emphasis in Survey Sampling. Since that time Trent has developed specific expertise in Mobile and Smartphone Survey Designs and in the use of machine learning methods for developing sampling designs and adaptive survey protocols.

Trent currently serves the Director of the Center for Survey Research and as a full professor in the Department of Management Science and Information Systems at the University of Massachusetts Boston.

Trent is currently the Past President of the Midwest Association for Public Opinion and the incoming Conference Chair of the American Association of Public Opinion Research and has recently been named a 2017 Fellow of the American Statistical Association.

When Trent is not working or thinking about surveys, sampling, smartphones and research in general, you can find him playing resident prince to his two princesses or playing an action packed game of pickleball or tennis!

Not a Member Yet?

It’s never too early to set yourself up for successful analysis with support and training from expert statisticians. Just head over and sign up for Statistically Speaking. You'll get access to this training webinar, 100+ other stats trainings, a pathway to work through the trainings that you need — plus the expert guidance you need to build statistical skill with live Q&A sessions and an ask-a-mentor forum.

Tagged With: Complex Survey, sampling weights, selection probabilities, Statistical analysis, survey weights, weighting

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Reader Interactions

Comments

  1. rhithDix says

    October 17, 2017 at 1:51 pm

    Dieser sehr gute Gedanke fällt gerade übrigens
    crapp

    Reply

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