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Randomization of health facilities to arm was implemented using random number generation in Stata 10.1.
Randomisation will be implemented using random permuted blocks of size 4.
Heuristic searches were implemented using random addition sequence (100 repetitions) and tree bisection-reconnection (TBR) branch swapping procedure.
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To account for nesting of employees within sites and to model the site-level variables, mixed effects regression was implemented using a random intercepts model.
The procedure was implemented using the random Forest Library in R, with all default choices selected.
Population-based health surveillance on a national scale (40) would be ideally implemented using a random sample of sentinel sites.
For computational convenience the scaled-t and DE densities are represented as infinite mixtures of scaled normal densities (Andrews and Mallows 1974), and the finite-mixture priors are implemented using latent random Bernoulli variables linking effects to components of the mixtures.
Statistical inference on models was implemented using a Bayesian random effects approach [ 15].
The scheme is implemented using the well-known double random phase encoding technique.
In the literature, multilevel models include mixed-effects models, but to distinguish the two in this paper we use mixed-effects to refer to analyses containing both fixed and random effects (implemented using the R lmer function) and multilevel models to refer to our application of Gelman's approach – implemented using WinBUGS - that calculates variance components for all variables).
In this work, a memory efficient algorithm is developed to compute the random fields and implemented using the ShakeMap framework.
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