summary {mverse}

Display the multiverse table with results.

Description

This method returns the multiverse table displaying all universes defined by the multiverse. Each row corresponds to a universe and each column represents a branch.

Usage

## S3 method for class 'mverse'
summary(object, ...)

## S3 method for class 'lm_mverse'
summary(object, conf.int = TRUE, conf.level = 0.95, output = "estimates", ...)

## S3 method for class 'glm_mverse'
summary(object, conf.int = TRUE, conf.level = 0.95, output = "estimates", ...)

## S3 method for class 'glm.nb_mverse'
summary(object, conf.int = TRUE, conf.level = 0.95, output = "estimates", ...)

Arguments

object

a glm.nb_mverse object.

...

Ignored.

conf.int

When TRUE (default), the estimate output includes the confidence intervals.

conf.level

The confidence level of the confidence interval returned using conf.int = TRUE. Default value is 0.95.

output

The output of interest. The possible values are "estimates" ("e"), "df", "deviance" ("de"), and "aic" ("bic"). Alternatively, the first letters may be used. Default value is "estimates".

Details

When you pass a mverse objected fitted with model, the summary table includes results of the fitted models across the multiverse.

Value

a multiverse table as a tibble.

Examples

# Displaying the multiverse table without any fitted values.
hurricane_strength <- mutate_branch(
  NDAM,
  HighestWindSpeed,
  Minpressure_Updated_2014
)
mv <- create_multiverse(hurricane) %>%
  add_mutate_branch(hurricane_strength)
summary(mv)
## Displaying after adding a a filter branch.
hurricane_outliers <- filter_branch(
  !Name %in% c("Katrina", "Audrey", "Andrew"),
  !Name %in% c("Katrina"),
  !Name %in% c("Katrina"),
  TRUE # include all
)
mv <- add_filter_branch(mv, hurricane_outliers)
summary(mv)



# Displaying the multiverse table with \code{lm} models fitted.
hurricane_strength <- mutate_branch(
  NDAM,
  HighestWindSpeed,
  Minpressure_Updated_2014
)
y <- mutate_branch(
  alldeaths, log(alldeaths + 1)
)
hurricane_outliers <- filter_branch(
  !Name %in% c("Katrina", "Audrey", "Andrew"),
  TRUE # include all
)
model_specifications <- formula_branch(
  y ~ femininity,
  y ~ femininity + hurricane_strength
)
mv <- create_multiverse(hurricane) %>%
  add_filter_branch(hurricane_outliers) %>%
  add_mutate_branch(hurricane_strength, y) %>%
  add_formula_branch(model_specifications) %>%
  lm_mverse()
summary(mv)



# Displaying the multiverse table with \code{glm} models fitted.
hurricane_strength <- mutate_branch(
  NDAM,
  HighestWindSpeed,
  Minpressure_Updated_2014
)
hurricane_outliers <- filter_branch(
  !Name %in% c("Katrina", "Audrey", "Andrew"),
  TRUE # include all
)
model_specifications <- formula_branch(
  alldeaths ~ femininity,
  alldeaths ~ femininity + hurricane_strength
)
model_distributions <- family_branch(poisson)
mv <- create_multiverse(hurricane) %>%
  add_filter_branch(hurricane_outliers) %>%
  add_mutate_branch(hurricane_strength) %>%
  add_formula_branch(model_specifications) %>%
  add_family_branch(model_distributions) %>%
  glm_mverse()
summary(mv)



# Displaying the multiverse table with \code{glm.nb} models fitted.
hurricane_strength <- mutate_branch(
  NDAM,
  HighestWindSpeed,
  Minpressure_Updated_2014
)
hurricane_outliers <- filter_branch(
  !Name %in% c("Katrina", "Audrey", "Andrew"),
  TRUE # include all
)
model_specifications <- formula_branch(
  alldeaths ~ femininity,
  alldeaths ~ femininity + hurricane_strength
)
mv <- create_multiverse(hurricane) %>%
  add_filter_branch(hurricane_outliers) %>%
  add_mutate_branch(hurricane_strength) %>%
  add_formula_branch(model_specifications) %>%
  glm.nb_mverse()
summary(mv)