Tidy a(n) epi.2by2 object
Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
## S3 method for class 'epi.2by2'
tidy(x, parameters = c("moa", "stat"), ...)x |
A |
parameters |
Return measures of association ( |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
The tibble has a column for each of the measures of association
or tests contained in massoc or massoc.detail when epiR::epi.2by2() is called.
A tibble::tibble() with columns:
conf.high |
Upper bound on the confidence interval for the estimate. |
conf.low |
Lower bound on the confidence interval for the estimate. |
df |
Degrees of freedom used by this term in the model. |
p.value |
The two-sided p-value associated with the observed statistic. |
statistic |
The value of a T-statistic to use in a hypothesis that the regression term is non-zero. |
term |
The name of the regression term. |
estimate |
Estimated measure of association |
if (requireNamespace("epiR", quietly = TRUE)) {
library(epiR)
dat <- matrix(c(13, 2163, 5, 3349), nrow = 2, byrow = TRUE)
rownames(dat) <- c("DF+", "DF-")
colnames(dat) <- c("FUS+", "FUS-")
fit <- epi.2by2(
dat = as.table(dat), method = "cross.sectional",
conf.level = 0.95, units = 100, outcome = "as.columns"
)
tidy(fit, parameters = "moa")
tidy(fit, parameters = "stat")
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