multidimBias  R Documentation 
Multidimensional sensitivity analysis for different sources of bias, where the bias analysis is repeated within a range of values for the bias parameter(s).
multidimBias(
case,
exposed,
type = c("exposure", "outcome", "confounder", "selection"),
se = NULL,
sp = NULL,
bias_parms = NULL,
OR.sel = NULL,
OR_sel = NULL,
alpha = 0.05,
dec = 4,
print = TRUE
)
case 
Outcome variable. If a variable, this variable is tabulated against. 
exposed 
Exposure variable. 
type 
Implement analysis for exposure misclassification, outcome misclassification, unmeasured confounder, or selection bias. 
se 
Numeric vector of sensitivities. Parameter used with exposure or outcome misclassification. 
sp 
Numeric vector of specificities. Parameter used with exposure or outcome misclassification. Should be the same length as 'se'. 
bias_parms 
List of bias parameters used with unmeasured confounder. The list is made of 3 vectors of the same length:

OR.sel 
Deprecated; please use OR_sel instead. 
OR_sel 
Selection odds ratios, for selection bias implementation. 
alpha 
Significance level. 
dec 
Number of decimals in the printout. 
print 
A logical scalar. Should the results be printed? 
A list with elements:
obs.data 
The analyzed 2 x 2 table from the observed data. 
obs.measures 
A table of odds ratios and relative risk with confidence intervals. 
adj.measures 
Multidimensional corrected relative risk and/or odds ratio data. 
bias.parms 
Bias parameters. 
multidimBias(matrix(c(45, 94, 257, 945),
dimnames = list(c("HIV+", "HIV"), c("Circ+", "Circ")),
nrow = 2, byrow = TRUE),
type = "exposure",
se = c(1, 1, 1, .9, .9, .9, .8, .8, .8),
sp = c(1, .9, .8, 1, .9, .8, 1, .9, .8))
multidimBias(matrix(c(45, 94, 257, 945),
dimnames = list(c("HIV+", "HIV"), c("Circ+", "Circ")),
nrow = 2, byrow = TRUE),
type = "outcome",
se = c(1, 1, 1, .9, .9, .9, .8, .8, .8),
sp = c(1, .9, .8, 1, .9, .8, 1, .9, .8))
multidimBias(matrix(c(105, 85, 527, 93),
dimnames = list(c("HIV+", "HIV"), c("Circ+", "Circ")),
nrow = 2, byrow = TRUE),
type = "confounder",
bias_parms = list(seq(.72, .92, by = .02),
seq(.01, .11, by = .01), seq(.13, 1.13, by = .1)))
multidimBias(matrix(c(136, 107, 297, 165),
dimnames = list(c("Uveal Melanoma+", "Uveal Melanoma"),
c("Mobile Use+", "Mobile Use ")),
nrow = 2, byrow = TRUE),
type = "selection",
OR_sel = seq(1.5, 6.5, by = .5))
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