episensr (version 0.7.1)

probsens.irr: Probabilistic sensitivity analysis for exposure misclassification of person-time data and random error.

Description

Probabilistic sensitivity analysis to correct for exposure misclassification when person-time data has been collected.

Usage

probsens.irr(counts, pt = NULL, reps = 1000, seca.parms = list(dist =
  c("constant", "uniform", "triangular", "trapezoidal", "logit-logistic",
  "logit-normal"), parms = NULL), seexp.parms = NULL, spca.parms = list(dist
  = c("constant", "uniform", "triangular", "trapezoidal", "logit-logistic",
  "logit-normal"), parms = NULL), spexp.parms = NULL, corr.se = NULL,
  corr.sp = NULL, discard = TRUE, alpha = 0.05, dec = 4, print = TRUE)

Arguments

counts

A table or matrix where first row contains disease counts and second row contains person-time at risk, and first and second columns are exposed and unexposed observations, as: lll{ Exposed Unexposed Cases a b Person-time N1 N0 }

pt

A numeric vector of person-time at risk. If provided, counts must be a numeric vector of disease counts.

reps

Number of replications to run.

seca.parms

List defining the sensitivity of exposure classification among those with the outcome. The first argument provides the probability distribution function (uniform, triangular, trapezoidal, logit-logistic, or logit-normal) and the second its parameters as a

seexp.parms

List defining the sensitivity of exposure classification among those without the outcome.

spca.parms

List defining the specificity of exposure classification among those with the outcome.

spexp.parms

List defining the specifity of exposure classification among those without the outcome.

corr.se

Correlation between case and non-case sensitivities.

corr.sp

Correlation between case and non-case specificities.

discard

A logical scalar. In case of negative adjusted count, should the draws be discarded? If set to FALSE, negative counts are set to zero.

alpha

Significance level.

dec

Number of decimals in the printout.

print

A logical scalar. Should the results be printed?

Value

• A list with elements:
• obs.data
  The analysed 2 x 2 table from the observed data.
• obs.measures
  A table of observed incidence rate ratio with exact confidence interval.
• adj.measures
  A table of corrected incidence rate ratios.
• sim.df
  Data frame of random parameters and computed values.

References

Lash, T.L., Fox, M.P, Fink, A.K., 2009 Applying Quantitative Bias Analysis to Epidemiologic Data, pp.117--150, Springer.

Examples

set.seed(123)
# Exposure misclassification, non-differential
probsens.irr(matrix(c(2, 67232, 58, 10539000),
dimnames = list(c("GBS+", "Person-time"), c("HPV+", "HPV-")), ncol = 2),
reps = 20000,
seca.parms = list("trapezoidal", c(.4, .45, .55, .6)),
spca.parms = list("constant", 1))