Parameters from Hypothesis Testing
Parameters from Hypothesis Testing.
## S3 method for class 'PMCMR' model_parameters(model, ...) ## S3 method for class 'glht' model_parameters(model, ci = 0.95, exponentiate = FALSE, verbose = TRUE, ...)
model |
Object of class |
... |
Arguments passed to or from other methods. For instance, when
|
ci |
Confidence Interval (CI) level. Default to 0.95 (95%). |
exponentiate |
Logical, indicating whether or not to exponentiate the
the coefficients (and related confidence intervals). This is typical for,
say, logistic regressions, or more generally speaking: for models with log
or logit link. Note: standard errors are also transformed (by
multiplying the standard errors with the exponentiated coefficients), to
mimic behaviour of other software packages, such as Stata. For
|
verbose |
Toggle warnings and messages. |
A data frame of indices related to the model's parameters.
if (require("multcomp", quietly = TRUE)) {
# multiple linear model, swiss data
lmod <- lm(Fertility ~ ., data = swiss)
mod <- glht(
model = lmod,
linfct = c(
"Agriculture = 0",
"Examination = 0",
"Education = 0",
"Catholic = 0",
"Infant.Mortality = 0"
)
)
model_parameters(mod)
}
if (require("PMCMRplus", quietly = TRUE)) {
model <- kwAllPairsConoverTest(count ~ spray, data = InsectSprays)
model_parameters(model)
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