probsens.irr | R Documentation |

Probabilistic sensitivity analysis to correct for exposure misclassification when person-time data has been collected.
Non-differential misclassification is assumed when only the two bias parameters
`seca.parms`

and `spca.parms`

are provided. Adding the 2 parameters
`seexp.parms`

and `spexp.parms`

(i.e. providing the 4 bias parameters)
evaluates a differential misclassification.

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

`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:
| |||||||||

`pt` |
A numeric vector of person-time at risk. If provided, | |||||||||

`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, logit-normal, or beta) and the second its parameters as a vector. Logit-logistic and logit-normal distributions can be shifted by providing lower and upper bounds. Avoid providing these values if a non-shifted distribution is desired. constant: constant value, uniform: min, max, triangular: lower limit, upper limit, mode, trapezoidal: min, lower mode, upper mode, max, logit-logistic: location, scale, lower bound shift, upper bound shift, logit-normal: location, scale, lower bound shift, upper bound shift, beta: alpha, beta.
| |||||||||

`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 specificity 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. |

A list with elements:

`obs.data` |
The analyzed 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. |

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

```
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))
```

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