Professor Elly Kaizar will present on "Combining Data in a Single Analysis" at the American Association for the Advancement of Science (AAAS) Annual Meeting on February, 18, 2018 in Austin, TX. This meeting has been called the "largest and most widely recognized global science gathering." Kaizar is one of only four speaker's at this year's meeting from Ohio State.
Kaizar's session tackles challenges in modern survey science -- how can we make accurate estimates or predictions in the new world where survey participants are both potentially hard to find and overloaded with requests for their attention? Many researchers are turning to new types of survey methods, including relying on convenient and volunteer participants. But it's not clear if results based on such methods are accurate, or if we could obtain more precise estimates or predictions by adjusting these new approaches. Her contribution to the panel will be to draw parallels between this current situation in survey science and a similar statistical problem in medical experiments, and to highlight areas where the two fields may learn from each other.