rita_bootstrap: Assay Based Incidence Estimation With Survey Bootstrap...
In fellstat/rita: Incidence Estimation Using Recency Assays

rita_bootstrap

R Documentation

Assay Based Incidence Estimation With Survey Bootstrap Intervals

Description

Assay Based Incidence Estimation With Survey Bootstrap Intervals

Usage

rita_bootstrap(
  recent,
  undiagnosed,
  low_viral,
  hiv,
  tslt,
  ever_hiv_test,
  weights,
  rep_weights = NULL,
  rep_weight_type = c("BRR", "Fay", "JK1", "JK2", "JKn", "bootstrap", "other"),
  combined_weights = TRUE,
  tau = 2,
  frr = lag_avidity_frr()[1],
  test_history_population = c("undiagnosed", "negative"),
  assay_surv = lag_avidity_survival(tau * 365),
  diag_surv = NULL,
  treated = NULL,
  treat_surv = NULL,
  conf_level = 0.95,
  show_progress = TRUE,
  ...
)

Arguments

`recent`	Logical. Tests recent on assay.
`undiagnosed`	Logical. No previous diagnosis.
`low_viral`	Logical. Has low viral load (< 1000).
`hiv`	Logical. Is HIV positive.
`tslt`	Time since last HIV test (days).
`ever_hiv_test`	Subject has been tested for HIV in the past.
`weights`	Survey weights.
`rep_weights`	A data.frame of replicate weights. See survey::svrrepdesign
`rep_weight_type`	The type of resampling weights. See svrepdesign.
`combined_weights`	TRUE if the rep_weights already include the sampling weights. This is usually the case.
`tau`	long term cut-off (years).
`frr`	False recency rate among treatment naive non-elite controller non-AIDS individuals.
`test_history_population`	If undiagnosed, the testing histories of undiagnosed HIV+ people are used. If negative, the HIV- population is used.
`assay_surv`	Survival function vector for assay among treatment naive non-elite controller non-AIDS individuals.
`diag_surv`	time to diagnosis survival function vector.
`treated`	A logical vector indicating a subject is on treatment. Only needed in the case of the use of RITA2 screening.
`treat_surv`	Probability an individual diagnosed i days ago is not on treatment.
`conf_level`	confidence level for bootstrap interval.
`show_progress`	If TRUE, prints bootstrap progress. This may also be a callback function taking one parameter equal to the index of the current replicate.
`...`	additional parameters to svrepdesign.

Value

A data.frame with columns for the estimate, standard error, lower confidence bound and upper confidence bound. Rows are defined by:

1. 'incidence': The incidence. 2. 'residual_frr': The false recency rate accounting for the screening process. 3. 'omega_rs': The mean duration of recency up to tau accounting for the screening process. 4. 'P(R|S)' : The proportion of screened in individual who test recent. 5. 'P(S|H)' : The proportion of HIV+ individuals that are screened in. 6. 'P(H)' : HIV prevalence.

Examples

data("assay_data")
rep_weights <-  dplyr::select(assay_data, dplyr::contains("btwt"))
rita_bootstrap(
recent=assay_data$recent,
undiagnosed=assay_data$undiagnosed,
low_viral=assay_data$elite_cntr,
hiv=assay_data$hiv,
weights=assay_data$weights,
tslt=assay_data$tslt,
ever_hiv_test=assay_data$ever_hiv_test,
rep_weights = rep_weights,
rep_weight_type = "JK1"
)

fellstat/rita documentation built on April 11, 2022, 2:31 p.m.