# plot.episensr.probsens: Plot(s) of probabilistic bias analyses In episensr: Basic Sensitivity Analysis of Epidemiological Results

 plot.episensr.probsens R Documentation

## Plot(s) of probabilistic bias analyses

### Description

This takes a `probsens`-family object and produces the distribution plot of chosen bias parameters, as well as distribution of adjusted measures (with confidence interval).

### Usage

``````## S3 method for class 'episensr.probsens'
plot(
x,
parms = c("rr", "or", "rr_tot", "or_tot", "irr", "irr_tot", "seca", "seexp", "spca",
"spexp", "or_sel", "prev.exp", "prev.nexp", "risk"),
...
)
``````

### Arguments

 `x` An object of class "episensr.probsens" returned from the `episensr probsens`, `probsens.sel`, `probsens.conf`, `probsens.irr`, `probsens.irr.conf` functions. `parms` Choice between adjusted relative risk (`rr`) and odds ratio (`or`), total error relative risk and odds ratio (`rr_tot` and `or_tot`), `seca`, `seexp`, `spca`, `or_sel`, and `spexp`, `prev.exp`, `prev.nexp` and `risk`, `irr` and `irr_tot`. `...` Other unused arguments.

```probsens, probsens.sel, probsens.conf, probsens.irr, probsens.irr.conf```

### Examples

``````set.seed(123)
risk <- probsens(matrix(c(45, 94, 257, 945),
dimnames = list(c("BC+", "BC-"), c("Smoke+", "Smoke-")), nrow = 2, byrow = TRUE),
type = "exposure", reps = 20000,
seca.parms = list("trapezoidal", c(.75, .85, .95, 1)),
spca.parms = list("trapezoidal", c(.75, .85, .95, 1)))
plot(risk, "rr")

set.seed(123)
odds <- probsens(matrix(c(45, 94, 257, 945),
dimnames = list(c("BC+", "BC-"), c("Smoke+", "Smoke-")), nrow = 2, byrow = TRUE),
type = "exposure", reps = 20000,
seca.parms = list("beta", c(908, 16)),
seexp.parms = list("beta", c(156, 56)),
spca.parms = list("beta", c(153, 6)),
spexp.parms = list("beta", c(205, 18)),
corr.se = .8,
corr.sp = .8)
plot(odds, "seca")

set.seed(123)
select <- probsens.sel(matrix(c(136, 107, 297, 165),
dimnames = list(c("Melanoma+", "Melanoma-"), c("Mobile+", "Mobile-")),
nrow = 2, byrow = TRUE), reps = 20000,
or.parms = list("triangular", c(.35, 1.1, .43)))
plot(select, "or_sel")

set.seed(123)
conf <- probsens.conf(matrix(c(105, 85, 527, 93),
dimnames = list(c("HIV+", "HIV-"), c("Circ+", "Circ-")), nrow = 2, byrow = TRUE),
reps = 20000,
prev.exp = list("triangular", c(.7, .9, .8)),
prev.nexp = list("trapezoidal", c(.03, .04, .05, .06)),
risk = list("triangular", c(.6, .7, .63)),
corr.p = .8)
plot(conf, "prev.exp")

set.seed(123)
inc1 <- 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))
plot(inc1, "irr")

set.seed(123)
inc2 <- probsens.irr.conf(matrix(c(77, 10000, 87, 10000),
dimnames = list(c("D+", "Person-time"), c("E+", "E-")), ncol = 2),
reps = 20000,
prev.exp = list("trapezoidal", c(.01, .2, .3, .51)),
prev.nexp = list("trapezoidal", c(.09, .27, .35, .59)),
risk = list("trapezoidal", c(2, 2.5, 3.5, 4.5)),
corr.p = .8)
plot(inc2, "risk")
``````

episensr documentation built on Aug. 30, 2023, 5:09 p.m.