Summary Method for "seroincidence.by"
Objects
Source: R/summary.seroincidence.by.R
summary.seroincidence.by.Rd
Calculate seroincidence from output of the seroincidence calculator
est.incidence.by()
.
Usage
# S3 method for class 'seroincidence.by'
summary(
object,
confidence_level = 0.95,
showDeviance = TRUE,
showConvergence = TRUE,
...
)
Arguments
- object
A dataframe containing output of function
est.incidence.by()
.- confidence_level
desired confidence interval coverage probability
- showDeviance
Logical flag (
FALSE
/TRUE
) for reporting deviance (-2*log(likelihood) at estimated seroincidence. Default =TRUE
.- showConvergence
Logical flag (
FALSE
/TRUE
) for reporting convergence (see help foroptim()
for details). Default =FALSE
.- ...
Additional arguments affecting the summary produced.
Value
A summary.seroincidence.by
object, which is a tibble::tibble, with the following columns:
incidence.rate
maximum likelihood estimate oflambda
(seroincidence)CI.lwr
lower confidence bound for lambdaCI.upr
upper confidence bound for lambdaDeviance
(included ifshowDeviance = TRUE
) Negative log likelihood (NLL) at estimated (maximum likelihood)lambda
)nlm.convergence.code
(included ifshowConvergence = TRUE
) Convergence information returned bystats::nlm()
The object also has the following metadata (accessible throughbase::attr()
):
antigen_isos
Character vector with names of input antigen isotypes used inest.incidence.by()
Strata
Character with names of strata used inest.incidence.by()
Examples
library(dplyr)
xs_data <-
sees_pop_data_pk_100
curve <-
typhoid_curves_nostrat_100 %>%
filter(antigen_iso %in% c("HlyE_IgA", "HlyE_IgG"))
noise <-
example_noise_params_pk
# estimate seroincidence
est2 <- est.incidence.by(
strata = c("catchment"),
pop_data = xs_data,
curve_params = curve,
noise_params = noise,
antigen_isos = c("HlyE_IgG", "HlyE_IgA"),
#num_cores = 8 # Allow for parallel processing to decrease run time
)
#> Warning: curve_params is missing all strata variables, and will be used unstratified.
#>
#> To avoid this warning, specify the desired set of stratifying variables in the `curve_strata_varnames` and `noise_strata_varnames` arguments to `est.incidence.by()`.
#> Warning: noise_params is missing all strata variables, and will be used unstratified.
#>
#> To avoid this warning, specify the desired set of stratifying variables in the `curve_strata_varnames` and `noise_strata_varnames` arguments to `est.incidence.by()`.
# calculate summary statistics for the seroincidence object
summary(est2)
#> Seroincidence estimated given the following setup:
#> a) Antigen isotypes : HlyE_IgG, HlyE_IgA
#> b) Strata : catchment
#>
#> Seroincidence estimates:
#> # A tibble: 2 × 13
#> Stratum catchment n est.start incidence.rate SE CI.lwr CI.upr coverage
#> <chr> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Stratu… aku 53 0.1 0.140 0.0216 0.104 0.189 0.95
#> 2 Stratu… kgh 47 0.1 0.200 0.0301 0.149 0.268 0.95
#> # ℹ 4 more variables: log.lik <dbl>, iterations <int>, antigen.isos <chr>,
#> # nlm.convergence.code <ord>