View source: R/vartrack_prob_detect.R
| vartrack_prob_detect | R Documentation | 
This function calculates the probability of detecting the presence of a variant given a sample size and sampling strategy.
vartrack_prob_detect(
  n,
  t = NA,
  p_v1 = NA,
  omega,
  p0_v1 = NA,
  r_v1 = NA,
  c_ratio = 1,
  sampling_freq
)
| n | sample size (either of cross-section or per timestep) | 
| t | time step number (e.g., days) at which variant should be detected by. Default = NA (either  | 
| p_v1 | the desired prevalence to detect a variant by. Default = NA (either  | 
| omega | probability of sequencing (or other characterization) success | 
| p0_v1 | initial variant prevalence (# introductions / infected population size) | 
| r_v1 | logistic growth rate | 
| c_ratio | coefficient of detection ratio, calculated as the ratio of the coefficients of variant 1 to variant 2. Default = 1 (no bias) | 
| sampling_freq | the sampling frequency (must be either 'xsect' or 'cont') | 
scalar of detection probability
Shirlee Wohl, Elizabeth C. Lee, Bethany L. DiPrete, and Justin Lessler
Other variant detection functions: 
vartrack_prob_detect_cont(),
vartrack_prob_detect_xsect(),
vartrack_samplesize_detect_cont(),
vartrack_samplesize_detect_xsect(),
vartrack_samplesize_detect()
Other variant tracking functions: 
vartrack_cod_ratio(),
vartrack_prob_detect_cont(),
vartrack_prob_detect_xsect(),
vartrack_prob_prev_xsect(),
vartrack_prob_prev(),
vartrack_samplesize_detect_cont(),
vartrack_samplesize_detect_xsect(),
vartrack_samplesize_detect(),
vartrack_samplesize_prev_xsect(),
vartrack_samplesize_prev()
# Cross-sectional sampling
vartrack_prob_detect(p_v1 = 0.02, n = 100, omega = 0.8, c_ratio = 1, sampling_freq = 'xsect')
# Periodic sampling
vartrack_prob_detect(n = 158, t = 30, omega = 0.8, p0_v1 = 1/10000, 
r_v1 = 0.1, c_ratio = 1, sampling_freq = 'cont')
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