report (version 0.6.0)

report.lm: Reporting (General) Linear Models

Description

Create reports for (general) linear models.

Usage

# S3 method for lm
report(x, include_effectsize = TRUE, effectsize_method = "refit", ...)
# S3 method for lm
report_effectsize(x, effectsize_method = "refit", ...)
# S3 method for lm
report_table(x, include_effectsize = TRUE, ...)
# S3 method for lm
report_statistics(
  x,
  table = NULL,
  include_effectsize = TRUE,
  include_diagnostic = TRUE,
  ...
)
# S3 method for lm
report_parameters(
  x,
  table = NULL,
  include_effectsize = TRUE,
  include_intercept = TRUE,
  ...
)
# S3 method for lm
report_intercept(x, table = NULL, ...)
# S3 method for lm
report_model(x, table = NULL, ...)
# S3 method for lm
report_performance(x, table = NULL, ...)
# S3 method for lm
report_info(
  x,
  effectsize = NULL,
  include_effectsize = FALSE,
  parameters = NULL,
  ...
)
# S3 method for lm
report_text(x, table = NULL, ...)
# S3 method for merMod
report_random(x, ...)

Value

An object of class report().

Arguments

x

Object of class lm or glm.

include_effectsize

If FALSE, won't include effect-size related indices (standardized coefficients, etc.).

effectsize_method

See documentation for effectsize::effectsize().

...

Arguments passed to or from other methods.

table

Provide the output of report_table() to avoid its re-computation.

include_diagnostic

If FALSE, won't include diagnostic related indices for Bayesian models (ESS, Rhat).

include_intercept

If FALSE, won't include the intercept.

effectsize

Provide the output of report_effectsize() to avoid its re-computation.

parameters

Provide the output of report_parameters() to avoid its re-computation.

See Also

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()

Examples

# \donttest{
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))
# }

# \donttest{
# 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))
# }