report.lm | R Documentation |
Create reports for (general) linear models.
## S3 method for class 'lm'
report(x, include_effectsize = TRUE, effectsize_method = "refit", ...)
## S3 method for class 'lm'
report_effectsize(x, effectsize_method = "refit", ...)
## S3 method for class 'lm'
report_table(x, include_effectsize = TRUE, ...)
## S3 method for class 'lm'
report_statistics(
x,
table = NULL,
include_effectsize = TRUE,
include_diagnostic = TRUE,
...
)
## S3 method for class 'lm'
report_parameters(
x,
table = NULL,
include_effectsize = TRUE,
include_intercept = TRUE,
...
)
## S3 method for class 'lm'
report_intercept(x, table = NULL, ...)
## S3 method for class 'lm'
report_model(x, table = NULL, ...)
## S3 method for class 'lm'
report_performance(x, table = NULL, ...)
## S3 method for class 'lm'
report_info(
x,
effectsize = NULL,
include_effectsize = FALSE,
parameters = NULL,
...
)
## S3 method for class 'lm'
report_text(x, table = NULL, ...)
## S3 method for class 'merMod'
report_random(x, ...)
x |
Object of class |
include_effectsize |
If |
effectsize_method |
See documentation for
|
... |
Arguments passed to or from other methods. |
table |
Provide the output of |
include_diagnostic |
If |
include_intercept |
If |
effectsize |
Provide the output of |
parameters |
Provide the output of |
An object of class report()
.
Specific components of reports (especially for stats models):
report_table()
report_parameters()
report_statistics()
report_effectsize()
report_model()
report_priors()
report_random()
report_performance()
report_info()
report_text()
Other types of reports:
report_system()
report_packages()
report_participants()
report_sample()
report_date()
Methods:
as.report()
Template file for supporting new models:
report.default()
library(report)
# Linear models
model <- lm(Sepal.Length ~ Petal.Length * Species, data = iris)
r <- report(model)
r
summary(r)
as.data.frame(r)
summary(as.data.frame(r))
# Logistic models
model <- glm(vs ~ disp, data = mtcars, family = "binomial")
r <- report(model)
r
summary(r)
as.data.frame(r)
summary(as.data.frame(r))
# Mixed models
library(lme4)
model <- lme4::lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris)
r <- report(model)
r
summary(r)
as.data.frame(r)
summary(as.data.frame(r))
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