BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//Tendenci - The Open Source AMS for Associations//Tendenci Codeba se MIMEDIR//EN BEGIN:VEVENT DESCRIPTION:--- This iCal file does *NOT* confirm registration.\r\nEvent d etails subject to change. ---\r\nhttps://www.statisticswithoutborders.org/ events/5/\r\n\r\nEvent Title: An Introduction to Small Area Estimation\r\n Start Date / Time: May 12, 2022 12:00 PM US/Eastern\r\nLocation: Virtual E vent\r\nSpeaker: Dr. Carolina Franco\r\nPresenter: Dr. Carolina Franco, Pr incipal Statistician, NORC at the University of Chicago, USA\r\nSmall area estimation (SAE) techniques can lead to greatly improved estimates relati ve to direct survey estimates when there is a large number of domains of i nterest and a limited overall sample size, which is often the case in surv eys. When successfully applied, SAE can dramatically reduce measures of un certainty and provide estimates for domains with no survey data. It can al low for publishing of official estimates at lower levels of aggregation. We will discuss the following topics: What is small area estimation (SAE)? What are the potential benefits of SAE? Examples of real applications of small area estimation\; An introduction to area-level and unit-level model s\;\; Discussion of frequently used software.--- This iCal file does *NOT* confirm registration.Event details subject to change. ---\r\n\r\n--- By T endenci - The Open Source AMS for Associations ---\r\n UID:uid5@statisticswithoutborders.org SUMMARY:An Introduction to Small Area Estimation DTSTART:20220512T160000Z DTEND:20220512T180000Z CLASS:PUBLIC PRIORITY:5 DTSTAMP:20240329T141342Z TRANSP:OPAQUE SEQUENCE:0 LOCATION:Virtual Event X-ALT-DESC;FMTTYPE=text/html:
Small area estimati on (SAE) techniques can lead to greatly improved estimates relative to dir ect survey estimates when there is a large number of domains of interest a nd a limited overall sample size, which is often the case in surveys. When successfully applied, SAE can dramatically reduce measures of uncertainty and provide estimates for domains with no survey data. It can allow for p ublishing of official estimates at lower levels of aggregation. \; We will discuss the following topics: \;What is small area estimation (SA E)? What are the potential benefits of SAE? Examples of real applications of small area estimation\; An introduction to area-level and unit-level mo dels\;\; Discussion of frequently used software.