This method returns the multiverse table displaying all universes defined by the multiverse. Each row corresponds to a universe and the columns include universe number, branch option name, and branch option definition.
# 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", ...)a glm.nb_mverse object.
Ignored.
When TRUE (default), the estimate output
includes the confidence intervals.
The confidence level of the confidence interval
returned using conf.int = TRUE. Default value is 0.95.
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".
a multiverse table as a tibble.
When you pass a mverse objected fitted with model,
the summary table includes results of the fitted models
across the multiverse.
# \donttest{
# 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)
#> # A tibble: 3 × 3
#> universe hurricane_strength_branch hurricane_strength_branch_code
#> <fct> <fct> <fct>
#> 1 1 hurricane_strength_1 NDAM
#> 2 2 hurricane_strength_2 HighestWindSpeed
#> 3 3 hurricane_strength_3 Minpressure_Updated_2014
## Displaying after adding a a filter branch.
hurricane_outliers <- filter_branch(
!Name %in% c("Katrina", "Audrey", "Andrew"),
!Name %in% c("Katrina"),
TRUE # include all
)
mv <- add_filter_branch(mv, hurricane_outliers)
summary(mv)
#> # A tibble: 9 × 5
#> universe hurricane_strength_br…¹ hurricane_outliers_b…² hurricane_strength_b…³
#> <fct> <fct> <fct> <fct>
#> 1 1 hurricane_strength_1 hurricane_outliers_1 NDAM
#> 2 2 hurricane_strength_1 hurricane_outliers_2 NDAM
#> 3 3 hurricane_strength_1 hurricane_outliers_3 NDAM
#> 4 4 hurricane_strength_2 hurricane_outliers_1 HighestWindSpeed
#> 5 5 hurricane_strength_2 hurricane_outliers_2 HighestWindSpeed
#> 6 6 hurricane_strength_2 hurricane_outliers_3 HighestWindSpeed
#> 7 7 hurricane_strength_3 hurricane_outliers_1 Minpressure_Updated_2…
#> 8 8 hurricane_strength_3 hurricane_outliers_2 Minpressure_Updated_2…
#> 9 9 hurricane_strength_3 hurricane_outliers_3 Minpressure_Updated_2…
#> # ℹ abbreviated names: ¹hurricane_strength_branch, ²hurricane_outliers_branch,
#> # ³hurricane_strength_branch_code
#> # ℹ 1 more variable: hurricane_outliers_branch_code <fct>
# }
# \donttest{
# 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 ~ MasFem,
y ~ MasFem + 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)
#> # A tibble: 60 × 16
#> universe hurricane_outliers_branch hurricane_strength_branch y_branch
#> <fct> <fct> <fct> <fct>
#> 1 1 hurricane_outliers_1 hurricane_strength_1 y_1
#> 2 1 hurricane_outliers_1 hurricane_strength_1 y_1
#> 3 2 hurricane_outliers_1 hurricane_strength_1 y_1
#> 4 2 hurricane_outliers_1 hurricane_strength_1 y_1
#> 5 2 hurricane_outliers_1 hurricane_strength_1 y_1
#> 6 3 hurricane_outliers_1 hurricane_strength_1 y_2
#> 7 3 hurricane_outliers_1 hurricane_strength_1 y_2
#> 8 4 hurricane_outliers_1 hurricane_strength_1 y_2
#> 9 4 hurricane_outliers_1 hurricane_strength_1 y_2
#> 10 4 hurricane_outliers_1 hurricane_strength_1 y_2
#> # ℹ 50 more rows
#> # ℹ 12 more variables: model_specifications_branch <fct>, term <chr>,
#> # estimate <dbl>, std.error <dbl>, statistic <dbl>, p.value <dbl>,
#> # conf.low <dbl>, conf.high <dbl>, hurricane_outliers_branch_code <fct>,
#> # hurricane_strength_branch_code <fct>, y_branch_code <fct>,
#> # model_specifications_branch_code <fct>
# }
# \donttest{
# 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 ~ MasFem,
alldeaths ~ MasFem + 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)
#> # A tibble: 30 × 16
#> universe hurricane_outliers_b…¹ hurricane_strength_b…² model_specifications…³
#> <fct> <fct> <fct> <fct>
#> 1 1 hurricane_outliers_1 hurricane_strength_1 model_specifications_1
#> 2 1 hurricane_outliers_1 hurricane_strength_1 model_specifications_1
#> 3 2 hurricane_outliers_1 hurricane_strength_1 model_specifications_2
#> 4 2 hurricane_outliers_1 hurricane_strength_1 model_specifications_2
#> 5 2 hurricane_outliers_1 hurricane_strength_1 model_specifications_2
#> 6 3 hurricane_outliers_1 hurricane_strength_2 model_specifications_1
#> 7 3 hurricane_outliers_1 hurricane_strength_2 model_specifications_1
#> 8 4 hurricane_outliers_1 hurricane_strength_2 model_specifications_2
#> 9 4 hurricane_outliers_1 hurricane_strength_2 model_specifications_2
#> 10 4 hurricane_outliers_1 hurricane_strength_2 model_specifications_2
#> # ℹ 20 more rows
#> # ℹ abbreviated names: ¹hurricane_outliers_branch, ²hurricane_strength_branch,
#> # ³model_specifications_branch
#> # ℹ 12 more variables: model_distributions_branch <fct>, term <chr>,
#> # estimate <dbl>, std.error <dbl>, statistic <dbl>, p.value <dbl>,
#> # conf.low <dbl>, conf.high <dbl>, hurricane_outliers_branch_code <fct>,
#> # hurricane_strength_branch_code <fct>, …
# }
# \donttest{
# Displaying the multiverse table with \code{glm.nb} models fitted.
hurricane_outliers <- filter_branch(
!Name %in% c("Katrina", "Audrey", "Andrew"),
TRUE # include all
)
model_specifications <- formula_branch(alldeaths ~ MasFem)
mv <- create_multiverse(hurricane) %>%
add_filter_branch(hurricane_outliers) %>%
add_formula_branch(model_specifications) %>%
glm.nb_mverse()
summary(mv)
#> # A tibble: 4 × 12
#> universe hurricane_outliers_branch model_specifications_branch term estimate
#> <fct> <fct> <fct> <chr> <dbl>
#> 1 1 hurricane_outliers_1 model_specifications_1 (Inte… 2.38
#> 2 1 hurricane_outliers_1 model_specifications_1 MasFem 0.0855
#> 3 2 hurricane_outliers_2 model_specifications_1 (Inte… 2.23
#> 4 2 hurricane_outliers_2 model_specifications_1 MasFem 0.201
#> # ℹ 7 more variables: std.error <dbl>, statistic <dbl>, p.value <dbl>,
#> # conf.low <dbl>, conf.high <dbl>, hurricane_outliers_branch_code <fct>,
#> # model_specifications_branch_code <fct>
# }