| simulate_pps_fast {prevtoinc} | R Documentation | 
Faster method to generate data for PPS with only length of nosocomial infections as output
Description
The function 'simulate_pps_fast' can be used to generate PPS data. This functions simulates a PPS on the basis of a given prevalence 'P' using a vector of probabilities 'dist.X.loi' for the values 1:length(dist.X.loi) of X.loi. It directly samples the time of infection up to date based on 'dist.X.loi'. Optionally, the length of stay is sampled independently ( treating the marginal distributions of length of stay and length of infection as independent by assumption) using 'dist.X.los' which is in the same format as 'dist.X.loi'. Because of this non-joint sampling rows should not be interpreted as individual patients.
Usage
simulate_pps_fast(n.sample, P, dist.X.loi, dist.X.los = NA,
  one.factor.loi = 1, one.factor.los = 1)
Arguments
| n.sample | number of beds to simulate | 
| P | prevalence of nosocomial infections | 
| dist.X.loi | vector of probabilities for values 1:length(dist.X.loi) of X.loi | 
| dist.X.los | vector of probabilities for values 1:length(dist.X.los) of X.los | 
| one.factor.loi | factor by which to approx. reduce number of one day observations for A.loi | 
| one.factor.los | factor by which to approx. reduce number of one day observations for A.los | 
Value
data frame with a row for a each simulated patient and the following columns
- A.loi - length of infection up to PPS 
- L.loi - total length of infection 
- A.los - length of stay up to PPS 
- L.los - total length of stay 
- patient.type - patient type (fixed to 1 for fast method) 
Examples
example.dist <- create_dist_vec(function(x) dpois(x-1, 7), 70)
data.pps.fast <- simulate_pps_fast(n.sample=5000,
                                  P=0.05,
                                  dist.X.loi = example.dist)
head(data.pps.fast)