Analysis of diagnostic tests without a gold standard reference
Usage
nogoldstandard(
data,
test1,
test1Positive,
test2,
test2Positive,
test3,
test3Positive,
test4,
test4Positive,
test5,
test5Positive,
method = "latent_class",
bootstrap = FALSE,
nboot = 1000,
alpha = 0.05
)Arguments
- data
The data as a data frame.
- test1
First diagnostic test variable.
- test1Positive
The positive level for Test 1.
- test2
Second diagnostic test variable.
- test2Positive
The positive level for Test 2.
- test3
Third diagnostic test variable (optional).
- test3Positive
The positive level for Test 3.
- test4
Fourth diagnostic test variable (optional).
- test4Positive
The positive level for Test 4.
- test5
Fifth diagnostic test variable (optional).
- test5Positive
The positive level for Test 5.
- method
Method for analyzing tests without gold standard.
- bootstrap
Calculate bootstrap confidence intervals.
- nboot
Number of bootstrap samples for confidence intervals.
- alpha
Alpha level for confidence intervals.
Value
A results object containing:
results$prevalence | a table | ||||
results$test_metrics | a table | ||||
results$model_fit | a table | ||||
results$agreement_plot | an image |
Tables can be converted to data frames with asDF or as.data.frame. For example:
results$prevalence$asDF
as.data.frame(results$prevalence)