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Computing Optimal Strata Bounds Using Dynamic Programming

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  • Eric Miller

    ()
    (Summit Consulting)

Abstract

Stratification is a sampling design that can improve efficiency. It works by first partitioning the population into homogeneous subgroups and then performing simple random sampling within each group. For a continuous variable, stratification involves determining strata boundaries. Holding the number of strata fixed, a reduction in the width of a given stratum reduces its associated variance at the expense of the variances from the other strata. Dynamic programming provides a method for simultaneously minimizing all of the strata variances by determining optimal strata boundaries. This presentation describes a new user-written command, optbounds, that uses dynamic programming to find optimal boundary points for a continuous stratification variable. The command makes use of the variance minimization technique developed by Khan, Nand, and Ahmad (2008, Survey Methodology 34: 205-214). The user first chooses a known probability distribution that approximates the stratification variable. Parameter estimates are then generated from the data and goodness of fit statistics are used to assess the quality of the approximation. A brief overview of the theory, a description of the command and several illustrative examples will be provided.

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File URL: http://fmwww.bc.edu/repec/san2012/miller.san2012.pdf
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Bibliographic Info

Paper provided by Stata Users Group in its series SAN12 Stata Conference with number 7.

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Date of creation: 01 Aug 2012
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Handle: RePEc:boc:scon12:7

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Web page: http://stata.com/meeting/sandiego12/
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