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Uncertainty Estimation Simon Cousens and Richard Silverwood.

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Presentation on theme: "Uncertainty Estimation Simon Cousens and Richard Silverwood."— Presentation transcript:

1 Uncertainty Estimation Simon Cousens and Richard Silverwood

2 Overview an implementation/coding issue with the Loess approach accounting for within-source correlation increasing uncertainty with increasing sources(?)

3 Implementation issue Murray at al. describe incorporation of two sources of uncertainty – random noise in data points through resampling parameter values using point estimates and variance- covariance matrix - (one aspect of) model uncertainty through use of a range of α values Wardlaw subsequently noted surprisingly narrow uncertainty ranges for Belarus, Congo, Cote dIvoire, Ukraine

4 Example: Congo

5 Example: Belarus

6 Accounting for within source correlation Loess and spline approaches have assumed independence of data points In practice multiple data points used in analysis derived from a single source (e.g. DHS) and assumption of independence likely to be violated One approach is to fit a multi-level model. Loess model: log(y ij ) = β 0j + β 1 x ij +β 2 z ij + e ij where β 0j = β 0 + u j and u j ~ N(0,σ u )

7 Results In general, little change in point estimates (e.g. 2010)

8 Results Uncertainty ranges within period of observed data increase (e.g. 1990)

9 Results Pattern less clear outside period of observed data (e.g. 2010)

10 Some specific country examples Costa Rica

11 Some specific country examples Sierra Leone

12 Increasing uncertainty with increasing sources? Eritrea



15 Comoros

16 The Gambia

17 Bangladesh

18 No obvious asymtotic pattern – is this useable in any way?

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