prevtoinc (version 0.12.0)

calculate_I_smooth: Estimate the incidence based on PPS data using monotone estimators for the distribution of A.

Description

Estimate incidence from PPS by the method proposed in the companion paper. `data` should be supplied as a data frame with at least a column named `A.loi` giving lengths of infection up to date of PPS. Values of zero for `A.loi` indicate absence of a HAI. Optionally, the data frame can also contain a column `A.los` supplying lengths of stay up to PPS to estimate x.los with the same method as well. If `correct.one` is `TRUE`, the number infections on their first day will be augmented to be at least as high as the number of infections on their second day for the estimation of x.loi .

Usage

calculate_I_smooth(data, method = "gren", correct.one.loi = "no",
  correct.one.los = "no")

Arguments

data

data frame which contains a column `A.loi` with lengths of nosocomial infections up to survey point ( zero if none) and possibly a column `A.los` with length of stay up to survey point

method

method to use for smoothing ("gren" ( Grenander ) or "rear" (rearrangement))

correct.one.loi

use correction for underreporting of one day LOIs: "no" if none, "fill.ones" to set the one-day cases to be at least the number of two-day cases, "start.two" to only use P(A=2| A > 1) as a proxy for P(A=1)

correct.one.los

use correction for underreporting of one day LOSs: "no" if none, "fill.ones" to set the one-day cases to be at least the number of two-day cases, "start.two" to only use P(A=2| A > 1) as a proxy for P(A=1)

Value

one-row data frame with following columns

• n - number of patients sampled

• n.noso - number of HAIs

• P.hat - estimate of prevalence P

• I.hat - estimate of incidence rate I

• I.pp.hat - estimate of incidence proportion per admission I.pp

• x.loi.hat - estimate of x.loi

• x.los.hat - estimate of x.los

• method - name of the method

Examples

# NOT RUN {
# create example data for PPS
example.dist <- create_dist_vec(function(x) dpois(x-1, 7), max.dist = 70)
example.dist.los <- create_dist_vec(function(x) dpois(x-1, lambda = 12),
                                    max.dist = 70)
data.pps.fast <- simulate_pps_fast(n.sample=200,
                                   P=0.05,
                                   dist.X.loi = example.dist,
                                   dist.X.los = example.dist.los)
head(data.pps.fast)

# estimate of incidence
calculate_I_smooth(data = data.pps.fast,
                   method = "gren")


# }