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Model-Assisted Small Area Estimation Using Mixed-Effects Random Forests

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Uzair A.
Model-Assisted Small Area Estimation Using Mixed-Effects Random Forests

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We are looking forward to the July edition of the Karachi R User Meetup, sponsored by Stat Devs and R Consortium

Agenda for the Talk:

Join the Karachi R User Group for an insightful talk on “Model-Assisted Small Area Estimation Using Mixed Effects Random Forest” presented by Muhammad Hamza.

This session will unpack the need for Small Area Estimation (SAE), the advantages of using ML algorithms over traditional methods, and the key distinctions between unit-level and area-level models.

We’ll explore design-based, model-based, and model-assisted frameworks, with a focus on implementing Mixed-Effects Random Forests in R. Practical applications using health indicators from the Demographic and Health Surveys (DHS) will also be showcased.

Whether you’re a data scientist, statistician, or policymaker, this talk will offer valuable insights into producing reliable estimates for data-limited regions with hands-on experience in R.

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