An R package that provides (very unofficial) add-on functionality to the NOMINATE-VoteView Project's wnominate package. Functions included in the package extract/output the coordinates and angles of roll call cutting lines, ie, the data underyling plots generated by wnominate::plot.cutlines() and wnominate::plot.angles(), respectively.
wnomadds analogue functions are dubbed wnm_get_cutlines() and wnm_get_angles(); both functions are based on existing wnominate code, tweaked only to output data frames as opposed to base R plots. wnomadds::wnm_get_cutlines() includes the added functionality of allowing users to add arrows at the end of cutting lines to specify roll call polarity.
library(devtools)
devtools::install_github("jaytimm/wnomadds")
library(wnomadds)To demonstrate the functionality and utility of the wnomadds package, we first quickly walk through the NOMINATE ideal points estimation procedure using roll call data from the 53rd Congress of the New Mexico State Legislature (via the nmlegisdatr package).
library(nmlegisdatr)#devtools::install_github("jaytimm/nmlegisdatr")
library(tidyverse)
library(wnominate)
library(pscl)wide_rolls <- nmlegisdatr::nml_rollcall %>%
filter(Chamber =='House') %>%
mutate(Bill_Unique = paste0(Bill_Code, substr(Motion, 1,1))) %>%
dplyr::select(Representative, Bill_Unique, Member_Vote) %>%
mutate(Member_Vote = case_when(Member_Vote == "Yea" ~ 1,
Member_Vote == "Nay" ~ 6,
Member_Vote %in% c("Excused", "Absent", "Rec") ~ 9)) %>%
spread(key= Bill_Unique, value = Member_Vote)roll_obj <- pscl::rollcall(wide_rolls [,-1],
yea = 1,
nay = 6,
missing = 9,
notInLegis = NA,
vote.names = colnames(wide_rolls)[2:ncol(wide_rolls)],
legis.names = wide_rolls$Representative)ideal_2d <- wnominate::wnominate (roll_obj,
ubeta=15,
uweights=0.5,
dims=2,
minvotes=20,
lop=0.025,
trials=3,
polarity=c('TOWNSEND', 'REHM'),
verbose=FALSE)
##
## Preparing to run W-NOMINATE...
##
## Checking data...
##
## All members meet minimum vote requirements.
##
## Votes dropped:
## ... 612 of 803 total votes dropped.
##
## Running W-NOMINATE...
##
## Getting bill parameters...
## Getting legislator coordinates...
## Starting estimation of Beta...
## Getting bill parameters...
## Getting legislator coordinates...
## Starting estimation of Beta...
## Getting bill parameters...
## Getting legislator coordinates...
## Getting bill parameters...
## Getting legislator coordinates...
## Estimating weights...
## Getting bill parameters...
## Getting legislator coordinates...
## Estimating weights...
## Getting bill parameters...
## Getting legislator coordinates...
##
##
## W-NOMINATE estimation completed successfully.
## W-NOMINATE took 8.27 seconds to execute.row.names(ideal_2d$rollcalls) <- colnames(wide_rolls)[2:ncol(wide_rolls)]house_data <- ideal_2d$legislators %>%
bind_cols(nml_legislators %>%
filter(Chamber == 'House')) The wnm_get_cutlines() function returns a data frame of cutting line coordinates. The function takes a nomObj object and a rollcall object (from call to pscl::rollcall). If the add_arrows parameter is set to TRUE, additionally included in the data frame are coordinates of points perpendicular to cutting line ends in the direction of maximum Yea's (per roll call). The distance between these points and the cutting line (ie, arrow length) can be specified by the arrow_length parameter.
with_cuts <- wnomadds::wnm_get_cutlines(ideal_2d,
rollcall_obj = roll_obj,
add_arrows = TRUE,
arrow_length = 0.05)Output effectively contains four sets of points:
- x_1, y_1: cutting line start
- x_2, y_2: cutting line end
- x_1a, y_1a: point perpendicular to cutting line start,
arrow_lengthaway in the direction of max Yea's - x_2a, y_2a: point perpendicular to cutting line end,
arrow_lengthaway in the direction of max Yea's
head(with_cuts)
## Bill_Code x_1 y_1 x_2 y_2 x_1a
## 1: R17_HB0004P 0.4787966 0.8779259 -0.3051518 -0.9523037 0.3872851
## 2: R17_HB0011P 0.4833821 0.8754095 -0.5342280 -0.8453404 0.3973446
## 3: R17_HB0016P -0.8637753 0.5038772 -0.9080242 -0.4189177 -0.8176356
## 4: R17_HB0017P -0.8498559 0.5270151 -0.9031616 -0.4293008 -0.8020401
## 5: R17_HB0028P 0.8640101 0.5034744 0.7760351 -0.6306897 0.8073019
## 6: R17_HB0032P 0.7934022 0.6086978 0.7599459 -0.6499863 0.7304680
## y_1a x_2a y_2a
## 1: 0.9171233 -0.3966633 -0.9131063
## 2: 0.9262900 -0.6202655 -0.7944599
## 3: 0.5016647 -0.8618844 -0.4211302
## 4: 0.5243498 -0.8553458 -0.4319661
## 5: 0.5078732 0.7193269 -0.6262909
## 6: 0.6103706 0.6970117 -0.6483135The four sets of points included in the output of wnomadds::get_cutlines can be used to create three line segments via geom_plot: cutting start to cutting end, cutting start to opposite arrow, and cutting end to opposite arrow.
ggplot () +
wnomadds::scale_color_party() +
theme(legend.position = 'bottom') +
annotate("path",
x=cos(seq(0,2*pi,length.out=300)),
y=sin(seq(0,2*pi,length.out=300)),
color='lightgray',
size = .25) +
geom_point(data=house_data,
aes(x=coord1D, y=coord2D,color = Party),
size= 3,
shape= 17) +
geom_segment(data=with_cuts,
aes(x = x_1, y = y_1, xend = x_2, yend = y_2)) + #cutting start to end
geom_segment(data=with_cuts,
aes(x = x_2, y = y_2, xend = x_2a, yend = y_2a), #cutting end to opposite arrow
arrow = arrow(length = unit(0.2,"cm"))) +
geom_segment(data=with_cuts,
aes(x = x_1, y = y_1, xend = x_1a, yend = y_1a), #cutting start to opposite arrow
arrow = arrow(length = unit(0.2,"cm")))+
geom_text(data=with_cuts,
aes(x = x_1a, y = y_1a, label = Bill_Code),
size=2.5,
nudge_y = 0.03,
check_overlap = TRUE) +
coord_fixed(ratio=1) +
labs(title="Lower Chamber: Cutting lines & legislator coordinates")
#select_cuts <- with_cuts$Bill_Code[112:123]
select_cuts <- c('R18_HB0079', 'R17_HB0442', 'R17_HB0017',
'R17_HB0086', 'R17_HB0125', 'R17_HB0527')
sub <- nmlegisdatr::nml_rollcall %>%
filter(Bill_Code %in% select_cuts) %>%
inner_join(house_data) %>%
inner_join(nml_legislation)
cut_sub <- subset(with_cuts, Bill_Code %in% paste0(select_cuts,'P')) %>%
mutate(Bill_Code = gsub('.$', '', Bill_Code)) %>%
inner_join(nml_legislation) sub %>%
ggplot(aes(x=coord1D, y=coord2D)) +
annotate("path",
x=cos(seq(0,2*pi,length.out=300)),
y=sin(seq(0,2*pi,length.out=300)),
color='lightgray',
size = .25) +
geom_point(aes(color = Party_Member_Vote,
shape= Party_Member_Vote,
fill = Party_Member_Vote),
size= 1.5) +
wnomadds::scale_color_rollcall() +
wnomadds::scale_fill_rollcall() +
wnomadds::scale_shape_rollcall() +
theme(legend.position = 'bottom') +
geom_text(aes(label=Representative),
size=1.75,
check_overlap = TRUE,
hjust = "inward",
nudge_y = -0.03)+
coord_fixed() +
geom_segment(data=cut_sub,
aes(x = x_1, y = y_1, xend = x_2, yend = y_2)) +
geom_segment(data=cut_sub,
aes(x = x_2, y = y_2, xend = x_2a, yend = y_2a),
arrow = arrow(length = unit(0.2,"cm"))) +
geom_segment(data=cut_sub,
aes(x = x_1, y = y_1, xend = x_1a, yend = y_1a),
arrow = arrow(length = unit(0.2,"cm")))+
geom_text(data=cut_sub,
aes(x = .7, y = -1, label = Bill_Code),
size=2.25,
nudge_y = 0.1,
check_overlap = TRUE) +
labs(title="Lower Chamber: Selected roll calls & cutting lines") +
facet_wrap(~Bill_Title, labeller = label_wrap_gen(), ncol = 3) +
theme(strip.text = element_text(size=7))
Cutting line angles can be extracted from a nomObj object using wnomadds::wnm_get_angles(). Output is a simple data frame.
angles <- wnomadds::wnm_get_angles(ideal_2d)
head(angles)
## Bill_Code angle
## 1 R17_HB0004P 66.81293
## 2 R17_HB0011P 59.40095
## 3 R17_HB0016P 87.25472
## 4 R17_HB0017P 86.80960
## 5 R17_HB0028P 85.56456
## 6 R17_HB0032P 88.47742