report (version 0.1.0)

report.estimate_contrasts: Estimated Means, Contrasts, Slopes and Smooth Report

Description

Create a report of an object from the estimate package.

Usage

# S3 method for estimate_contrasts
report(model, effsize = "funder2019", ...)
# S3 method for estimate_means
report(model, effsize = "funder2019", ...)
# S3 method for estimate_slopes
report(model, effsize = "funder2019", ...)
# S3 method for estimate_smooth
report(model, ...)

Arguments

model

Object of class estimate.

effsize

Interpret the standardized parameters using a set of rules. Default corresponds to "funder2019" for linear models and "chen2010" for logistic models.

...

Arguments passed to or from other methods.

See Also

report

Examples

# NOT RUN {
library(estimate)
library(report)
library(lme4)

data <- iris
data$Group <- ifelse(data$Sepal.Width > 3, "A","B")

model <- lm(Petal.Width ~ Species * Group, data = data)
report(estimate_contrasts(model))
# }
# NOT RUN {
library(rstanarm)

model <- stan_glm(Sepal.Width ~ Species * Petal.Width, data = iris)
report(estimate_contrasts(model))
report(estimate_contrasts(model, fixed = "Petal.Width"))
report(estimate_contrasts(model, modulate = "Petal.Width", length = 2))
# }
# NOT RUN {
# }
# NOT RUN {
library(estimate)
library(rstanarm)

model <- stan_glm(Sepal.Width ~ Species * Petal.Width, data = iris)
report(estimate_means(model))
report(estimate_means(model, modulate = "Petal.Width"))
# }
# NOT RUN {
library(rstanarm)
model <- stan_glm(Sepal.Width ~ Species * Petal.Width, data = iris)
report(estimate_slopes(model))
# }
# NOT RUN {
library(rstanarm)
model <- stan_glm(Sepal.Width ~ poly(Petal.Length, 2), data = iris)
report(estimate_smooth(model))
# }