Department seminar by Mohammad Jafari Jozani, University of ManitobaExport this event to calendar

Thursday, March 15, 2018 — 4:00 PM EDT

Quantile regression with nominated samples for  more efficient and less expensive follow-up studies of bone mineral density


We develop a new methodology for analyzing upper and/or lower quantiles of the distribution of bone mineral density using quantile regression. Nomination sampling designs are used to obtain more representative samples from the tails of the underlying distribution.  We propose new check functions to incorporate the rank information of nominated samples in the estimation process.  Also, we provide an alternative approach that translates estimation problems with nominated samples to corresponding problems under simple random sampling (SRS). Strategies are given to choose proper nomination sampling designs for a given population quantile.  We implement our results to a large cohort study in Manitoba to analyze quantiles of bone mineral density using available covariates. We show that in some cases, methods based on nomination sampling designs require about one tenth of the sample used in SRS to estimate the lower or upper tail conditional quantiles with comparable mean squared errors. This is a dramatic reduction in time and cost compared with the usual SRS approach.

Location 
M3 - Mathematics 3
Room: 3127
200 University Avenue West
Waterloo, ON N2L 3G1
Canada

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