ExampleData | R Documentation |

A synthetic dataset mimicking a realistic hierarchical sampling frame. Simulated samples are taken from across three regions (A, B, and C) in which the vectors have a low (0.5%), medium (2%), and high (4%) prevalence of the marker of interest. Ten villages are chosen within each region, and traps are placed at ten sites within each village. Every site is sampled once a year over three years (0, 1, and 2). Prevalence is not uniform within each region or over time. At baseline (year 0), prevalence varies between villages within each region around the mean for the region, and prevalence varies between sites within each village around the mean for the village. Consequently though the prevalence is different for each site, two sites within the same village are likely to have a more similar prevalence than two sites in different villages, or two sites in different regions. On average the prevalence is declining over time (odds ratio of 0.8 per year), however, the growth rate varies between villages. Consequently two sites in different villages with similar prevalence at baseline may have different prevalence by the third year, and prevalence may go up in some villages. Each year the traps at each site catch a negative binomial number (mean 200, dispersion 5) of vectors. The catch size at each site and year is independent. Each year, the catches at each site are pooled into groups of 25 with an additional pool for any remainder (e.g. a catch of 107 vectors will be pooled into 4 pools of 25 and one pool of 7). Test results on each pool are simulated assuming the test has perfect sensitivity and specificity.

ExampleData

A data frame with 6 variables:

- NumInPool
Number of specimens in pool. Range = 1:25

- Region
ID of the region the pool was taken from. "A", "B", or "C"

- Village
ID of village that pool was taken from. Includes name of region e.g. "B-3" is village 3 from region B

- Site
ID of site that pool was taken from. Includes name of region and village e.g. "B-3-7" is site 7 from village 3 from region B

- Result
Result of test on pool; 0 = negative, 1 = positive

- Year
Year of sampling. Years are 0, 1, or 2

The 'true' model can be summarised in formula notation as:

Result ~ Region + Year + (1+Year|Village) + (1|Site)

where the coefficient for Year is log(0.8), the standard deviation for intercept random effects for village and site are both 0.5, the standard deviation for the year random effect for village is 0.2 and the random effects are all uncorrelated/independent.

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