A simulated dataset containing the number of human cases of campylobacteriosis, the numbers of source samples positive for Campylobacter for each bacterial subtype, and the overall source prevalence.
sim_SAA list containing the human cases (`cases'), source samples (`sources'), prevalences (`prev') and true values (`truevals').
cases: data frame with 364 rows and 4 variables:
number of human cases of campylobacteriosis
Time id for the samples
Location id for the samples
MLST type id for the samples
sources: data frame with 1092 rows and 4 variables
number of source samples positive for campylobacteriosis
Time id for the samples
Source id for the samples
MLST type id for the samples
prev: data frame with 12 rows and 3 variables
Prevalence value (number of positive samples divided by total number of samples)
Time id for the samples
Source id for the samples
truevals: list containing a long format data frame for each model parameter giving the true value of that parameter.
A dataframe with 24 rows and 4 variables: Value contains the true alpha values, Time, Location and Source contain the time, location and source id's respectively.
A dataframe with 91 rows and 2 variables: Value contains the true q values, and Type contains the type id's.
A dataframe with 364 rows and 4 variables: Value contains the true lambda_i values, Time, Location and Type contain the time, location and type id's respectively.
A dataframe with 24 rows and 4 variables: Value contains the true xi values, Time, Location and Source contain the time, location and source id's respectively.
A dataframe with 2184 rows and 5 variables: Value contains the true r values, Time, Type, Location and Source contain the time, type, location and source id's respectively.