id_plot_legis_var: Plot Legislator/Person Over-time Variances

Description Usage Arguments Details Examples

View source: R/Plot.R

Description

This function can be used on a fitted idealstan object to plot the over-time variances (average rates of change in ideal points) for all the persons/legislators in the model.

Usage

1
2
3
4
5
id_plot_legis_var(object, return_data = FALSE, include = NULL,
  high_limit = 0.95, low_limit = 0.05, text_size_label = 2,
  text_size_group = 2.5, point_size = 1, hjust_length = -0.7,
  person_labels = TRUE, group_labels = F, person_ci_alpha = 0.1,
  group_color = TRUE, ...)

Arguments

object

A fitted idealstan object

return_data

If true, the calculated legislator/bill data is returned along with the plot in a list

include

Specify a list of person/legislator IDs to include in the plot (all others excluded)

high_limit

The quantile (number between 0 and 1) for the high end of posterior uncertainty to show in plot

low_limit

The quantile (number between 0 and 1) for the low end of posterior uncertainty to show in plot

text_size_label

ggplot2 text size for legislator labels

text_size_group

ggplot2 text size for group text used for points

point_size

If person_labels and group_labels are set to FALSE, controls the size of the points plotted.

hjust_length

horizontal adjustment of the legislator labels

person_labels

if TRUE, use the person_id column to plot labels for the person (legislator) ideal points

group_labels

if TRUE, use the group column to plot text markers for the group (parties) from the person/legislator data

person_ci_alpha

The transparency level of the dot plot and confidence bars for the person ideal points

group_color

If TRUE, give each group/bloc a different color

...

Other options passed on to plotting function, currently ignored

Details

This function will plot the person/legislator over-time variances as a vertical dot plot with associated high-density posterior interval (can be changed with high_limit and low_limit options).

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
# To demonstrate, we load the 114th Senate data and fit a time-varying model

data('senate114_fit')

## Not run: 
senate_data <- id_make(senate114,outcome = 'cast_code',
person_id = 'bioname',
item_id = 'rollnumber',
group_id= 'party_code',
time_id='date',
miss_val='Absent')

 senate114_time_fit <- id_estimate(senate_data,
 model_type = 2,
 use_vb = T,
 fixtype='vb_partial',
 vary_ideal_pts='random_walk',
 restrict_ind_high = "WARREN, Elizabeth",
 restrict_ind_low="BARRASSO, John A.",
 seed=84520)
# We plot the variances for all the Senators

id_plot_legis_var(senate114_fit)

## End(Not run)

saudiwin/idealstan documentation built on July 12, 2019, 4:24 a.m.