The Social & Economic Survey Research Institute (SESRI) at Qatar University (QU) held a workshop on “Advanced Sampling” on October 10-13, aimed to introduce researchers to the principles and practice of analyzing data from complex sample surveys.
The event brought together over 40 participants across QU to exchange their ideas and knowledge, and to share their experiences on complex sample survey data. SESRI Director Dr Hassan Al-Sayed delivered the opening remarks.
The workshop was led by Professor and Research Professor Emeritus at the University of Michigan and Research Professor and Joint Program in Survey Methodology at the University of Maryland Prof James M Lepkowski, and Senior Research Associate in the Survey Methodology Program at the Institute for Social Research Prof Patricia Berglund. They presented the principles of survey design and how design features affect analysis methods as well as the use of statistical software to do such analysis. They also illustrated methods for analyzing survey data with such features through examples using an education survey from Qatar, and implemented such analyses using two statistical software systems -- SPSS and Stata.
In his remarks, Dr Hassan Al-Sayed noted that complex sample surveys are those employing one or more basic sampling design or estimation techniques such as weights, stratification, cluster sampling, nonlinear estimation, variance estimation, or imputation. He further noted that the nature of these features are examined to help participants understand why these features make analysis of such data more complex.
He added: “By hosting this event, SESRI is working towards QU’s strategic objective to seek efficient solutions to issues that impact the wider community and to ensure that research efforts address contemporary challenges in Qatar and beyond. SESRI continues to deliver on its mission to enhance research capacity by studying and monitoring important societal changes, and to provide sound and reliable data to guide policy formulation, priority-setting, and evidence-based planning and research in the social and economic sectors.”
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