Programs > Eurasia Program > Events


December 10th 2012

SSRC Eurasia Program Webinar Series: Issues in Quantitative Methods in Eurasian Studies

The SSRC Eurasia Program is pleased to announce the first installment in the new Webinar Series on Issues in Quantitative Methods in Eurasia Studies. Following on from the Eurasia Program’s two summer 2012 Workshops in Quantitative Methods, the SSRC will offer 4 online, interactive webinars aimed at increasing the quantitative skills of researchers of Eurasia. These webinars will be led by Dr. Jane Zavisca, associate professor of sociology at the University of Arizona. In addition to a PhD in sociology, she has an MA and postdoctoral training in statistics. She has designed two original surveys in Russia, as well as worked with secondary surveys such as RLMS and GGS. December 10th, 2012 3PM EST To register, click here: https://www3.gotomeeting.com/register/912107590 Understanding and Adjusting for Complex Sample Designs in the Eurasian Context This webinar will introduce the principles of and rationale for complex survey designs, provide an illustration of the steps involved in designing such a sample, and offer practical advice on how to identify and adjust for complex designs when performing statistical analysis. Examples and advice given will be tailored for the Eurasian context. Participants need only have a basic background in statistics (i.e. an introductory graduate-level course that covers simple linear regression). Most large-scale surveys employ complex sample designs, including multistage samples with clustering and/or stratification, and oversampling of subpopulations. Yet researchers routinely fail to correctly adjust for sample design when performing statistical analyses. Most graduate curricula in quantitative methods present statistical techniques that assume a simple random sample, as does statistical software by default. Incorrect assumptions can lead to incorrect estimates of both sample statistics (e.g. means, regression coefficients) and their standard errors.