plot.ob_decompose {ddecompose} | R Documentation |

## Plot decomposition terms for quantiles

### Description

The function plots decomposition terms for quantiles estimtated
with `ob_decompose`

over the unit interval.

### Usage

```
## S3 method for class 'ob_decompose'
plot(
x,
...,
detailed_effects = TRUE,
aggregate_factors = TRUE,
custom_aggregation = NULL,
confidence_bands = FALSE,
confidence_level = 0.95
)
```

### Arguments

`x` |
an object of class "ob_decompose", usually, a result of a call to [ob_decompose()] with [statistics = "quantiles"]. |

`...` |
other parameters to be passed through to plot function. |

`detailed_effects` |
If 'TRUE' (default), then the detailed effects are plotted. Otherwise only the total (aggregate) effects are plotted. |

`aggregate_factors` |
boolean, if 'TRUE' (default) terms associated with detailed factor levels are aggregated to a single term for every factor variable. |

`custom_aggregation` |
list specifying the aggregation of detailed decomposition terms. The parameter 'custom_aggregation' overrides the parameter 'aggregate_factors'. If 'NULL' (default), then either all detailed terms or all terms associated with a single variable are returned. |

`confidence_bands` |
If 'TRUE' and if standard errors have been bootstrapped, confidence bands are plotted. |

`confidence_level` |
numeric value between 0 and 1 (default = 0.95) that defines the confidence interval
plotted as a ribbon and defined as |

### Value

a ggplot illustrating the decomposition terms for quantiles.

### Examples

```
data("nlys00")
mod1 <- log(wage) ~ age + central_city + msa + region + black +
hispanic + education + afqt + family_responsibility + years_worked_civilian +
years_worked_military + part_time + industry
# plotting RIF regression decomposition of deciles
decompose_rifreg_deciles <- ob_decompose(
formula = mod1,
data = nlys00,
group = female,
reweighting = TRUE,
rifreg_statistic = "quantiles",
bootstrap = TRUE,
bootstrap_iterations = 50,
reference_0 = FALSE
)
plot(decompose_rifreg_deciles)
plot(decompose_rifreg_deciles,
confidence_bands = TRUE
)
# plotting Oaxaca-Blinder decomposition
decompose_ob_mean <- ob_decompose(
formula = mod1,
data = nlys00,
group = female,
reweighting = TRUE,
bootstrap = FALSE,
reference_0 = FALSE
)
plot(decompose_ob_mean)
plot(decompose_ob_mean, detailed_effects = FALSE)
# With custom aggregation
custom_aggregation <- list(
`Age, race, region, etc.` = c(
"age",
"blackyes",
"hispanicyes",
"regionNorth-central",
"regionSouth",
"regionWest",
"central_cityyes",
"msayes"
),
`Education` = c(
"education<10 yrs",
"educationHS grad (diploma)",
"educationHS grad (GED)",
"educationSome college",
"educationBA or equiv. degree",
"educationMA or equiv. degree",
"educationPh.D or prof. degree"
),
`AFTQ` = "afqt",
`L.T. withdrawal due to family` = "family_responsibility",
`Life-time work experience` = c(
"years_worked_civilian",
"years_worked_military",
"part_time"
),
`Industrial sectors` = c(
"industryManufacturing",
"industryEducation, Health, Public Admin.",
"industryOther services"
)
)
plot(decompose_ob_mean, custom_aggregation = custom_aggregation)
```

*ddecompose*version 1.0.0 Index]