Builds the claim card that falsifyr attacks: term, estimate, uncertainty, p-value, confidence interval, and kill-rule metadata.
Usage
extract_claim(model, term = NULL, ...)
# Default S3 method
extract_claim(model, term = NULL, ...)
# S3 method for class 'lm'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)
# S3 method for class 'glm'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)
# S3 method for class 'htest'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)
# S3 method for class 'anova'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)
# S3 method for class 'aov'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)
# S3 method for class 'merMod'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)
# S3 method for class 'coxph'
extract_claim(
model,
term = NULL,
alpha = 0.05,
alternative = c("two.sided", "less", "greater"),
kill_rule = "p_over_alpha",
effect_threshold = NULL,
...
)Arguments
- model
A fitted model or hypothesis-test object.
- term
Character scalar naming the coefficient or test term.
- ...
Additional arguments passed to methods.
- alpha
Significance level stored on the extracted claim.
- alternative
Character scalar defining the claim direction for coefficient tests:
"two.sided","less", or"greater".- kill_rule
Character scalar naming the kill rule to store on the extracted claim.
- effect_threshold
Numeric threshold stored on the claim for
"effect_below_threshold".