Weisberg_and_Rusk_Shepard_Plot.r -- R
Program to Replicate Weisberg and RuskHere is what Weisberg_and_Rusk_Shepard_Plot.r looks like:
#
#
#
# Weisberg_and_Rusk.r -- Replicates Famous 1970 W&R paper in APSR
#
# ***See Homework #5 2003 Houston MEASUREMENT THEORY Course***
# http://voteview.org/measure.htm
#
# wallace wallace therm
# humphrey humphrey thermometer
# nixon nixon thermometer
# mccarthy mccarthy thermometer
# reagan reagan thermometer
# rockefeller rockefeller thermometer
# lbj lbj thermometer
# romney romney thermometer
# kennedy robert kennedy thermometer
# muskie muskie thermometer
# agnew agnew thermometer
# lemay "bombs away with Curtis LeMay" thermometer
#
# Read Just The Thermometer Data From 1968 Survey
#
# Remove all objects just to be safe
#
rm(list=ls(all=TRUE))
library(MASS)
library(stats)
#
T <- matrix(scan("C:/ucsd_homework_6/therm68.txt",0),ncol=12,byrow=TRUE)
#
nrow <- length(T[,1])
ncol <- length(T[1,])
#
#
# Labels For Candidates
#
junk <- NULL
junk[1] <- "Wallace"
junk[2] <- "Humphrey"
junk[3] <- "Nixon"
junk[4] <- "McCarthy"
junk[5] <- "Reagan"
junk[6] <- "Rockefeller"
junk[7] <- "LBJ"
junk[8] <- "Romney"
junk[9] <- "Kennedy"
junk[10] <- "Muskie"
junk[11] <- "Agnew"
junk[12] <- "LeMay"
#
# The range of the 1968 Feeling Thermometers was 0 to 97 -- 98 and 99
# were used as missing values. You need to tell R that 98 and 99 are
# missing. To do this, use the following command:
#
# If T[i,j] = 98 or 99 set TT[i,j] = NA (missing data)
# else if set TT[i,j] = T[i,j]
#
TT <- ifelse(T==98 | T==99,NA,T)
#
# To compute the correlation matrix use the command below:
# The "pairwise.complete.obs" tells R to throw away missing
# data pair-wise, not list-wise (that is, the whole row of data!).
#
R <- cor(TT,use="pairwise.complete.obs")
RR <- R
#
#
# Transform the Correlation Matrix to Distance Matrix
#
i <- 0
while (i < ncol) {
i <- i + 1
j <- 0
while (j < ncol) {
j <- j + 1
#
# This is the Normal Transformation
#
RR[i,j] <- (1 - R[i,j])
#
#
}
}
#
# Call Classical Kruskal-Young-Shepard-Torgerson Non-Metric
# Multidimensional Scaling Program
#
# RR -- Input
# dim=2 -- number of dimensions
# y -- starting configuration (generated internally)
#
# Scale in two dimensions
#
kdim <- 2
y <- rep(0,kdim*ncol)
dim(y) <- c(ncol,kdim)
#
# Call Kruskal NonMetric MDS
#
wandrnmds <- isoMDS(RR,y=cmdscale(RR,kdim),kdim, maxit=50)
# as.dist transforms a square symmetric matrix of distances
RR.dist <- as.dist(RR,diag=FALSE,upper=FALSE) into a distance object. This is necessary for the Shepard(...) routine
shepardcheck.sh <- Shepard(RR.dist,wandrnmds$points) Shepard is an undocumented function in R
plot(shepardcheck.sh, type="n",asp=1,main="",xlab="",ylab="", I figured this out by trial and error!!
xlim=c(0,2),ylim=c(0,2),font=2) I copied the syntax from the bottom of the isoMDS page!!
points(shepardcheck.sh$x, shepardcheck.sh$y,pch=16,col="red") The key is to use the lower left triangle distance matrix from
# the as.dist function.
# The "S" means "stair-steps"
#
lines(shepardcheck.sh$x, shepardcheck.sh$yf,lty=1,lwd=2,type = "S",font=2)
#
# Main title
mtext("Shepard Diagram for MDS Solution\nWeisberg and Rusk",side=3,line=1.00,cex=1.2,font=2)
# x-axis title
mtext("Observed Dissimilarities",side=1,line=2.75,font=2,cex=1.2)
# y-axis title
mtext("Estimated Dissimilarities (D-hats)",side=2,line=2.75,font=2,cex=1.2)
#
#
# This creates another Graphics Device in R
#
windows()
xmax <- c(wandrnmds$points[,1],wandrnmds$points[,2])
axismax <- max(abs(xmax))
#
plot(wandrnmds$points[,1],wandrnmds$points[,2],type="n",asp=1,
main="",
xlab="",ylab="",
xlim=c(-axismax,axismax),ylim=c(-axismax,axismax),font=2)
#
# Main title
mtext("The 1968 Candidate Configuration\nFrom MDS Program in R",side=3,line=1.00,cex=1.2,font=2)
# x-axis title
mtext("Liberal - Conservative",side=1,line=2.75,font=2,cex=1.2)
# y-axis title
mtext("Anti-Wallace Wallace",side=2,line=2.75,font=2,cex=1.2)
#
#
# pos -- a position specifier for the text. Values of 1, 2, 3 and 4,
# respectively indicate positions below, to the left of, above and
# to the right of the specified coordinates
#
namepos <- NULL
namepos[1] <- 2 # Wallace
namepos[2] <- 3 # Humphrey
namepos[3] <- 4 # Nixon
namepos[4] <- 2 # McCarthy
namepos[5] <- 4 # Reagan
namepos[6] <- 2 # Rockefeller
namepos[7] <- 3 # LBJ
namepos[8] <- 2 # Romney
namepos[9] <- 4 # Kennedy
namepos[10] <- 2 # Muskie
namepos[11] <- 4 # Agnew
namepos[12] <- 2 # LeMay
#
text(wandrnmds$points[,1],wandrnmds$points[,2],junk,pos=namepos,offset=0.5,col="blue",font=2)
points(wandrnmds$points[,1],wandrnmds$points[,2],pch=16,col="red",font=2)
text(-0.7,1.0,paste("Stress = ",
0.01*round(wandrnmds$stress, 2)),col="purple",font=2)
#
# This creates another Graphics Device in R
#
windows()
#
# Create Data For Gradient of Generalization Plots
#
#
y <- rep(0,((ncol*(ncol-1))/2)*2)
dim(y) <- c(((ncol*(ncol-1))/2),2)
#
i <- 1
kk <- 0
while (i <= ncol) {
j <- i
while (j <= ncol) {
k <- 0
dist <- 0.0
while (k < kdim) {
k <- k+1
dist <- dist + (wandrnmds$points[i,k]-wandrnmds$points[j,k])^2
}
if(i != j) {
kk <- kk +1
y[kk,1] <- dist
y[kk,2] <- R[i,j]
# y[kk,2] <- RR[i,j]
}
j <- j + 1
}
i <- i + 1
}
#
#
ylow <- min(y[,2])
yhigh <- max(y[,2])
plot(y[,1],y[,2],ylim=c(ylow,yhigh),
xlab="",ylab="",col="red",font=2)
lines(lowess(y[,1],y[,2],f=.2),lwd=3)
text(10,80,"Line estimated \nUsing Lowess")
#
# Main title
mtext("Shepard's Theory of Generalization\nWeisberg and Rusk Data",side=3,line=1.00,cex=1.2,font=2)
# x-axis title
mtext("Psychological Distance",side=1,line=2.75,font=2,cex=1.2)
# y-axis title
mtext("Observed Similarity",side=2,line=2.75,font=2,cex=1.2)
#
#
# Save The Shepard Graph Data Sorted Ascending
#
kp <- order(y[,2])
shepard <- cbind(y[kp,1],y[kp,2])
#
-
Run Weisberg_and_Rusk_Shepard_Plot.r and you will get the following three graphs:
- Turn in these three graphs.
- We are now going to compare our results from R
with those from KYST. To do this, we need to get
the Pearson Correlation matrix stored in the matrix R out into a file that
we can then submit to KYST. At the command line in
R type:
write.matrix(R,"c:/ucsd_homework_4/R-table2.txt") -- write.matrix writes a matrix to a file nicely formatted
Bring the file up in Epsilon. It should look like this:
Type in the names of the 12 candidates so that your file looks like this:
Now, use Epsilon to stack the following commands on top of the correlation matrix:TORSCA PRE-ITERATIONS=3 DIMMAX=3,DIMMIN=1 PRINT HISTORY,PRINT DISTANCES COORDINATES=ROTATE ITERATIONS=50 REGRESSION=DESCENDING DATA,LOWERHALFMATRIX,DIAGONAL=PRESENT,CUTOFF=-2.00 1968 FEELING THERMOMETER CORRELATION MATRIX 12 1 1 (12X,12F12.8)
and do not forget to put COMPUTE and STOP on the bottom!
Report the Stress Values for 1, 2, and 3 dimensions and use R to graph the results in two dimensions.
- Use R to produce a Shepard Diagram
for the two dimensional solution in the same format as
Homework 2 question 1.
(define-macro "hw4" "C-U41C-FC-KC-YC-AC-NC-XoC-XoC-YC-AC-XpC-U19C-FC-MC-PC-KC-YC-DC-AC-NC-XoC-YC-AC-EC-MC-XpC-Xp")
- Simply highlight the above, put it on the clipboard, and paste it into
Epsilon and save it in the same directory that
you have the output files for the color example. Below I assume that you call
the file macro_hw4.txt (but you can call it whatever you want).
- Now, bring up the
KYST coordinates in the top window, the color matrix
in a center window, and an empty window at the bottom. It should look like this:
- Make sure that you have positioned the cursor in the top window at the beginning
of the line for the first set of coordinates and positioned the cursor in the
middle window at the beginning of the line "434 INDIGO..." The Macro assumes that you
are starting it with the cursor in the top window a the beginning of the line with
the first set of coordinates.
- Now, to load the macro into Epsilon,
type:
Alt-X
and you will see Command: appear at the bottom of the screen. Now type:
load-buffer
and you should see:
Now hit Enter and type:
macro_hw4.txt
You should see:
- Now hit Enter and you should see
the following:
If you see 0 errors detected. then Epsilon is satisifed that the macro is a legal series of commands.
- Before continuing with executing the macro, note that
above what Epsilon wanted was the
name of a buffer -- that is, a file that it has
in its buffer list -- this is why you pulled macro_hw4.txt into
Epsilon earlier. If you forget the names of
files that you have been working with you can always see the
list of Epsilon
buffers by typing the command at any time:
C-XC-B (Manipulate a List of Buffers Command)
And you will see:
- To execute the macro one time type:
Alt-X then
hw4
You should see:
Now hit Enter and the macro executes one time and your screen should show this:
- To execute the macro multiple times use the
C-U command
(Set Numeric Argument Command);
namely, do the keystrokes:
C-U13Alt-Xhw4
and you will see:
- Now hit Enter and you will see:
- Save color_coords.txt and close the other two windows.
- Modify the Double_Center_color_circle.r program from Homework # 3
Problem 3 to read this file and make the plot. For example, the read commands should look like
this:
# # Remove all objects just to be safe # rm(list=ls(all=TRUE)) # library(MASS) # # rcx.file <- "c:/ucsd_homework_4/color_coords.txt" # # Standard fields and their widths # rcx.fields <- c("colorname","x1","x2") rcx.fieldWidths <- c(19,7,7) # # Read the vote data from fwf # U <- read.fwf(file=rcx.file,widths=rcx.fieldWidths,as.is=TRUE,col.names=rcx.fields) dim(U) ncolU <- length(U[1,]) T <- U[,2:ncolU] # # nrow <- length(T[,1]) ncol <- length(T[1,]) # colorx1 <- T[,1] colorx2 <- T[,2] # etc. etc. etc.
Make a plot of the color coordinates. Turn in the plot and your R code.
- Edit macro_hw4.txt so that you can use it to create the coordinate
file for Table 1.3 -- the similarities for nations. Call the macro
macro_hw4_2b.txt. Turn in this macro and the file that it creates.
NonMetric_MDS_Color_Circle.r -- Program to
run non-metric MDS on the Color Circle Data
Color_Circle.txt -- 14 Color Similarities Data#
# NonMetric_MDS_color_circle.r -- NonMetric MDS Program
#
#
# **************** The Eckman Color Data *****************
#
# 434 INDIGO 100 86 42 42 18 6 7 4 2 7 9 12 13 16
# 445 BLUE 86 100 50 44 22 9 7 7 2 4 7 11 13 14
# 465 42 50 100 81 47 17 10 8 2 1 2 1 5 3
# 472 BLUE-GREEN 42 44 81 100 54 25 10 9 2 1 0 1 2 4
# 490 18 22 47 54 100 61 31 26 7 2 2 1 2 0
# 504 GREEN 6 9 17 25 61 100 62 45 14 8 2 2 2 1
# 537 7 7 10 10 31 62 100 73 22 14 5 2 2 0
# 555 YELLOW-GREEN 4 7 8 9 26 45 73 100 33 19 4 3 2 2
# 584 2 2 2 2 7 14 22 33 100 58 37 27 20 23
# 600 YELLOW 7 4 1 1 2 8 14 19 58 100 74 50 41 28
# 610 9 7 2 0 2 2 5 4 37 74 100 76 62 55
# 628 ORANGE-YELLOW 12 11 1 1 1 2 2 3 27 50 76 100 85 68
# 651 ORANGE 13 13 5 2 2 2 2 2 20 41 62 85 100 76
# 674 RED 16 14 3 4 0 1 0 2 23 28 55 68 76 100
#
#
# Remove all objects just to be safe
#
rm(list=ls(all=TRUE))
#
library(MASS)
library(stats)
#
#
rcx.file <- "c:/ucsd_homework_4/color_circle.txt"
#
# Standard fields and their widths
#
rcx.fields <- c("colorname","x1","x2","x3","x4","x5",
"x6","x7","x8","x9","x10","x11","x12","x13","x14")
rcx.fieldWidths <- c(18,4,4,4,4,4,4,4,4,4,4,4,4,4,4)
#
# Read the vote data from fwf
#
U <- read.fwf(file=rcx.file,widths=rcx.fieldWidths,as.is=TRUE,col.names=rcx.fields)
dim(U)
ncolU <- length(U[1,])
T <- U[,2:ncolU]
TT <- ((100-T)/50)^2 Here is the Transformation into Distances
T <- TT
#
nrow <- length(T[,1])
ncol <- length(T[1,])
#
names <- c("434 Indigo","445 Blue","465","472 Blue-Green","490","504 Green","537",
"555 Yellow-Green","584","600 Yellow","610","628 Orange-Yellow",
"651 Orange","674 Red")
#
# pos -- a position specifier for the text. Values of 1, 2, 3 and 4,
# respectively indicate positions below, to the left of, above and
# to the right of the specified coordinates
#
namepos <- rep(2,nrow)
#
# The KYST routine does not like zero distances in the off-diagonal!!!
# Do Error Catch here if necessary
# This Error Catch is Necessary if
# If T[i,j] = 0 set TT[i,j] = .03 you have an off-diagonal term that is 0.0
# else if set TT[i,j] = T[i,j]
#
#TT <- ifelse(T==0,0.03,T)
#
#
# Call Classical Kruskal-Young-Shepard-Torgerson Non-Metric
# Multidimensional Scaling Program
#
# TT -- Input
# kdim=2 -- number of dimensions
# y -- starting configuration (generated internally)
#
kdim <- 2
y <- rep(0,kdim*nrow) The R routine is fussy about wanting
dim(y) <- c(nrow,kdim) y to be a declared matrix!
#
wandrnmds <- isoMDS(TT,y=cmdscale(TT,kdim),kdim, maxit=50)
#
xmax <- c(wandrnmds$points[,1],wandrnmds$points[,2])
axismax <- max(abs(xmax))
#
# ############################################
# Flip Signs of Dimensions as Necessary Here
# ############################################
#
xx <- -wandrnmds$points[,1]
yy <- -wandrnmds$points[,2]
#
#
plot(xx,yy,type="n",asp=1,
main="",
xlab="",
ylab="",
xlim=c(-axismax,axismax),ylim=c(-axismax,axismax),font=2)
#
text(-axismax+.10,axismax,paste("Stress = ", This is a nifty way to plot
0.01*round(wandrnmds$stress, 2)),col="purple",cex=1.2) the Stress Value
# R Puts Stress out as a Percentage
#
points(xx,yy,pch=16,col="red",font=2)
text(xx,yy,names,pos=namepos,offset=0.2,col="blue",font=2)
#
#
# Main title
mtext("The Color Circle \nFrom NonMetric MDS in R",side=3,line=1.25,cex=1.5,font=2)
# x-axis title
mtext("",side=1,line=2.75,cex=1.2,font=2)
# y-axis title
mtext("",side=2,line=2.5,cex=1.2,font=2)
#
- Tidy up the plot so it looks nice as you did in Problem 3 of Homework 3.
That is, change the values in namepos accordingly.
- Use Epsilon to change the number of dimensions
and run the program in 1, 3, 4, and 5 dimensions. Plot the Stress values for 1 - 5 dimensions
in the same fashion as you plotted the eigenvalues in Problem 3 of Homework 3.
Turn in the plot and the R code.
NonMetric_MDS_Color_Circle_2.r -- Program to
run non-metric MDS on the Color Circle Data
Color_Coords_2.txt -- Starting Coordinates for KYST#
# NonMetric_MDS_color_circle_2.r -- NonMetric MDS Program
#
#
# **************** The Eckman Color Data *****************
#
# 434 INDIGO 100 86 42 42 18 6 7 4 2 7 9 12 13 16
# 445 BLUE 86 100 50 44 22 9 7 7 2 4 7 11 13 14
# 465 42 50 100 81 47 17 10 8 2 1 2 1 5 3
# 472 BLUE-GREEN 42 44 81 100 54 25 10 9 2 1 0 1 2 4
# 490 18 22 47 54 100 61 31 26 7 2 2 1 2 0
# 504 GREEN 6 9 17 25 61 100 62 45 14 8 2 2 2 1
# 537 7 7 10 10 31 62 100 73 22 14 5 2 2 0
# 555 YELLOW-GREEN 4 7 8 9 26 45 73 100 33 19 4 3 2 2
# 584 2 2 2 2 7 14 22 33 100 58 37 27 20 23
# 600 YELLOW 7 4 1 1 2 8 14 19 58 100 74 50 41 28
# 610 9 7 2 0 2 2 5 4 37 74 100 76 62 55
# 628 ORANGE-YELLOW 12 11 1 1 1 2 2 3 27 50 76 100 85 68
# 651 ORANGE 13 13 5 2 2 2 2 2 20 41 62 85 100 76
# 674 RED 16 14 3 4 0 1 0 2 23 28 55 68 76 100
#
#
# Remove all objects just to be safe
#
rm(list=ls(all=TRUE))
#
library(MASS)
library(stats)
#
#
rcx.file <- "c:/ucsd_homework_4/color_circle.txt"
#
# Standard fields and their widths
#
rcx.fields <- c("colorname","x1","x2","x3","x4","x5",
"x6","x7","x8","x9","x10","x11","x12","x13","x14")
rcx.fieldWidths <- c(18,4,4,4,4,4,4,4,4,4,4,4,4,4,4)
#
# Read the vote data from fwf
#
U <- read.fwf(file=rcx.file,widths=rcx.fieldWidths,as.is=TRUE,col.names=rcx.fields)
dim(U)
ncolU <- length(U[1,])
T <- U[,2:ncolU]
TT <- ((100-T)/50)^2
T <- TT
#
nrow <- length(T[,1])
ncol <- length(T[1,])
#
rcx.file <- "c:/ucsd_homework_4/color_coords.txt"
# Here is the extra read --
# Standard fields and their widths Starting Coordinates are read in
#
rcx.fields <- c("colorname2","xx1","xx2")
rcx.fieldWidths <- c(19,7,7)
#
# Read the vote data from fwf
#
UU <- read.fwf(file=rcx.file,widths=rcx.fieldWidths,as.is=TRUE,col.names=rcx.fields)
dim(UU)
ncolUU <- length(UU[1,])
y <- as.matrix(UU[,2:ncolUU]) Note this -- R can be funny about
# data types
names <- c("434 Indigo","445 Blue","465","472 Blue-Green","490","504 Green","537",
"555 Yellow-Green","584","600 Yellow","610","628 Orange-Yellow",
"651 Orange","674 Red")
#
# pos -- a position specifier for the text. Values of 1, 2, 3 and 4,
# respectively indicate positions below, to the left of, above and
# to the right of the specified coordinates
#
namepos <- rep(2,nrow)
#
# The KYST routine does not like zero distances in the off-diagonal!!!
# Do Error Catch here if necessary
#
# If T[i,j] = 0 set TT[i,j] = .03
# else if set TT[i,j] = T[i,j]
#
#TT <- ifelse(T==0,0.03,T)
#
#
# Call Classical Kruskal-Young-Shepard-Torgerson Non-Metric
# Multidimensional Scaling Program
#
# TT -- Input
# kdim=2 -- number of dimensions
# y -- starting configuration (generated internally)
#
kdim <- 2
#y <- rep(0,kdim*nrow)
#dim(y) <- c(nrow,kdim)
#
wandrnmds <- isoMDS(TT,y,kdim, maxit=50) Contrast this with the previous version
#
xmax <- c(wandrnmds$points[,1],wandrnmds$points[,2])
axismax <- max(abs(xmax))
#
# ############################################
# Flip Signs of Dimensions as Necessary Here
# ############################################
#
xx <- -wandrnmds$points[,1]
yy <- -wandrnmds$points[,2]
#
#
plot(xx,yy,type="n",asp=1,
main="",
xlab="",
ylab="",
xlim=c(-axismax,axismax),ylim=c(-axismax,axismax),font=2)
#
text(-axismax+.10,axismax,paste("Stress = ",
0.01*round(wandrnmds$stress, 2)),col="purple",cex=1.2)
#
#
points(xx,yy,pch=16,col="red",font=2)
text(xx,yy,names,pos=namepos,offset=0.2,col="blue",font=2)
#
#
# Main title
mtext("The Color Circle \nFrom NonMetric MDS in R",side=3,line=1.25,cex=1.5,font=2)
# x-axis title
mtext("",side=1,line=2.75,cex=1.2,font=2)
# y-axis title
mtext("",side=2,line=2.5,cex=1.2,font=2)
#
- Tidy up the plot so it looks nice as you did in Problem 3 of Homework 3.
That is, change the values in namepos accordingly.
- Here is what the coordinate file looks like:
434 INDIGO -0.317 0.902 445 BLUE -0.368 0.818 465 -0.900 0.566 472 BLUE-GREEN -0.965 0.503 490 -0.988 -0.133 504 GREEN -0.828 -0.650 537 -0.547 -0.862 555 YELLOW-GREEN -0.310 -0.977 584 0.562 -0.736 600 YELLOW 0.830 -0.389 610 1.026 -0.074 628 ORANGE-YELLOW 1.006 0.227 651 ORANGE 0.914 0.346 674 RED 0.885 0.459
Use Epsilon to arbitrarily change some of the coordinates and run the program to see if you get back the same Stress value. Do this 5 times and turn in each plot and each set of starting coordinates.
HOUSYM3.EXE -- Agreement Score Program
SEN108KH.ORD -- 108th Senate Roll Call Data
SYMSTRT3.DAT -- Control Card File for Agreement
Score Programand place them in the same folder on a WINTEL machine. SYMSTRT3.DAT looks like this:
SEN108KH.ORD SEN108.DAT (36A1,1600I1) 675 36 20 0.025The first line is the name of the roll call matrix that the program will read and compute the agreement scores from. The second line is the name of the output file (its a good idea to name the output file something that you can remember!). The third line, in order, has the number of roll call votes (note that this number is always 4 digits -- in this case, 0675); the number of characters before the first roll call, 0036; the number of roll call votes a Senator would have to cast to be included in the output, 0020; and the minimum minority margin for the roll calls, 00.025. What this means is that all roll call votes 97-3 to 50-50 are included. This throws out unanimous, 100-0, and near unanimous roll calls (99-1 and 98-2).
If you analyzed a matrix with 1122 roll calls, the third line would be:
1122 36 20 0.025. At the command line type
HOUSYM3
The program should only take a few seconds to run and it produces two output files -- SEN108.DAT that you specified in the "control card" file, and a diagnostics file HOUSYM3.DAT:
1089991099 0USA 200 BUSH 100 95 88 87 91 97 83 31 36 7 14 95 86 10 16 20 21 21 25 96 95 11 10 96 92 12 92 24 95 96 9 96 92 97 98 48 31 74 65 9 7 6 4 13 14 12 93 95 93 95 93 19 96 95 65 96 14 90 91 8 8 14 93 10 13 4 93 24 20 92 87 93 96 93 10 98 83 59 7 16 90 14 14 95 97 95 93 95 97 18 10 95 90 18 13 19 13 19 17 93 95
1084970041 0ALABAMA 20001SESSIONS 95 100 91 86 89 94 80 25 29 12 18 93 85 14 19 19 25 13 20 92 89 13 17 92 91 11 88 27 89 91 13 90 90 92 92 43 30 75 73 15 10 12 10 15 12 17 86 90 91 90 89 35 92 88 49 92 20 87 89 14 12 19 90 14 17 10 91 25 22 83 85 92 94 87 19 93 78 67 13 18 91 18 19 91 89 92 88 89 90 19 15 90 88 18 17 16 16 16 17 92 94
1089465941 0ALABAMA 20001SHELBY 88 91 100 90 91 88 77 30 33 17 24 90 86 20 25 24 30 16 25 93 90 19 23 91 93 18 87 32 89 92 20 89 91 91 92 47 36 77 74 21 17 18 12 20 17 23 88 93 92 91 91 39 91 89 54 86 25 87 86 18 17 24 92 19 22 17 92 31 28 86 87 91 89 90 25 90 80 69 18 23 91 23 25 92 91 90 86 93 94 25 19 92 89 23 22 20 21 19 21 90 91
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1081550343 0FLORIDA 10001GRAHAM BOB 21 13 16 18 17 13 28 79 78 90 86 13 20 90 87 89 81 100 87 16 19 90 88 13 14 89 19 81 19 17 89 18 16 15 16 64 78 31 34 89 91 89 94 89 91 85 21 17 16 19 18 72 15 19 59 18 85 20 17 88 89 86 15 90 88 91 16 82 83 24 21 14 13 22 85 15 30 39 89 87 18 86 83 16 18 16 19 17 16 84 88 18 20 86 87 86 89 88 91 14 12
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1082952332 0KANSAS 20001BROWNBACK 96 90 89 89 92 89 80 31 34 15 22 91 88 19 22 23 29 18 25 94 92 17 20 94 92 17 88 32 91 93 18 100 95 94 93 47 35 78 75 20 16 16 13 20 18 22 89 93 90 92 91 40 93 92 54 87 24 85 87 18 16 23 93 17 21 17 92 30 27 87 87 92 89 89 23 89 81 70 16 20 90 23 25 92 93 92 90 93 93 25 18 90 90 21 22 19 21 21 23 91 90
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1081540651 0KENTUCK 20001BUNNING 97 92 91 91 92 91 77 29 32 13 20 93 90 17 22 21 28 15 23 94 92 14 18 95 94 15 89 30 92 94 16 94 94 100 95 47 34 77 74 18 13 13 11 18 15 21 90 94 92 94 94 38 94 92 53 88 22 85 87 16 14 22 94 16 19 14 95 29 25 86 88 95 92 90 21 91 79 70 14 18 91 21 23 95 92 95 89 93 95 22 16 93 90 19 20 18 19 17 19 94 95
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1081303952 0MARYLAN 10001SARBANES 7 10 17 20 17 8 21 82 78 94 88 11 21 94 88 88 81 91 88 14 19 93 91 13 14 94 18 78 16 16 93 16 16 13 14 64 79 31 34 94 100 95 95 92 94 88 20 16 15 16 16 74 14 18 60 14 89 17 11 93 93 87 17 93 89 95 16 82 86 24 19 13 9 22 88 11 28 39 94 87 15 90 89 16 15 13 18 16 15 85 91 15 19 90 90 90 91 87 89 11 10
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10814920 3 0MASSACH 10001KERRY JOHN 4 10 12 12 13 9 25 84 81 94 90 10 19 94 92 92 85 94 86 11 13 91 92 10 10 94 15 82 12 11 94 13 12 11 10 61 79 28 34 94 95 92 100 97 96 91 15 11 11 12 12 74 11 13 58 12 89 14 14 93 92 89 12 94 93 97 12 88 88 19 17 12 7 18 91 8 18 46 93 85 13 91 91 11 12 10 12 10 13 89 95 10 13 94 96 90 93 94 93 7 8
1082973223 0MICHIGA 10001STABENOW 13 15 20 23 21 13 25 84 83 92 88 15 26 91 88 89 82 89 88 17 23 90 88 16 17 92 22 83 21 21 90 20 20 18 18 65 80 33 37 94 92 89 97 100 93 89 25 20 18 22 20 77 18 22 64 18 89 19 15 91 90 87 20 92 91 93 21 84 88 27 22 17 13 26 90 15 31 40 91 83 19 91 90 20 19 17 22 19 19 83 92 19 23 92 93 87 89 87 91 14 14
1081470923 0MICHIGA 10001LEVIN CARL 14 12 17 20 18 11 24 83 81 91 86 13 22 91 88 89 83 91 87 15 20 92 88 13 14 93 19 81 18 18 91 18 18 15 17 65 79 31 34 92 94 91 96 93 100 88 23 17 16 20 18 73 15 19 60 16 87 16 14 91 92 86 17 92 88 93 18 82 85 26 21 14 12 23 88 14 28 39 92 85 17 89 87 18 17 16 20 16 17 83 90 17 20 89 90 89 90 88 90 13 11
1084010133 0MINNESO 10001DAYTON 12 17 23 26 23 15 26 83 80 89 85 18 26 86 86 85 78 85 84 20 26 86 85 19 21 87 24 78 23 23 89 22 23 21 21 65 81 36 38 90 88 85 91 89 88 100 27 22 20 25 23 76 21 23 63 19 88 19 17 87 86 84 22 88 87 89 24 81 86 27 24 19 16 30 87 17 31 39 86 83 22 90 90 22 21 18 23 22 22 80 87 21 24 88 89 83 88 85 88 17 17
1084030233 0MINNESO 20001COLEMAN 93 86 88 89 89 84 79 36 39 20 27 86 87 23 29 28 34 21 29 91 89 21 24 88 88 22 87 35 91 91 23 89 91 90 91 51 39 82 77 23 20 19 15 25 23 27 100 91 88 91 90 43 90 89 58 84 28 83 83 21 20 27 90 22 25 19 91 32 31 88 88 88 85 91 27 88 81 71 20 24 88 28 28 89 91 89 86 91 91 29 22 91 88 26 26 22 25 24 26 86 85
1081400946 0MISSISS 20001COCHRAN 95 90 93 92 96 89 77 32 34 16 22 91 90 20 24 23 30 17 25 94 92 17 21 93 93 18 90 32 92 94 18 93 94 94 96 48 35 78 76 20 16 16 11 20 17 22 91 100 93 93 94 40 95 92 54 86 24 87 86 18 16 24 95 18 20 17 92 31 28 87 89 93 90 90 22 90 81 71 16 21 89 24 25 95 93 94 89 95 95 24 17 92 91 21 21 20 20 17 22 91 92
1081403146 0MISSISS 20001LOTT 93 91 92 89 91 89 78 30 32 15 22 91 86 18 25 22 28 16 23 93 88 15 19 92 93 16 88 32 89 91 17 90 92 92 93 46 34 78 75 19 15 14 11 18 16 20 88 93 100 92 91 39 93 91 52 89 22 87 89 17 14 23 92 17 20 15 90 29 26 85 87 93 92 87 21 90 79 70 15 20 91 22 23 91 92 93 87 90 93 23 16 92 88 20 20 18 19 17 20 91 92
1082936934 0MISSOUR 20001TALENT 95 90 91 91 92 87 79 33 36 16 23 90 88 20 27 24 32 19 26 94 91 18 22 91 92 19 90 33 92 94 19 92 93 94 94 48 36 80 77 21 16 16 12 22 20 25 91 93 92 100 95 41 93 92 55 87 25 86 87 19 17 25 93 19 22 16 94 32 28 88 89 93 89 90 24 89 81 72 17 21 90 25 26 93 92 92 89 92 93 25 19 92 90 23 23 21 23 20 22 90 90
1081550134 0MISSOUR 20001BOND 93 89 91 92 92 88 77 32 35 16 23 91 89 20 25 22 31 18 26 92 90 17 22 92 92 18 88 33 91 94 18 91 93 94 95 49 36 79 76 21 16 16 12 20 18 23 90 94 91 95 100 40 93 90 55 86 25 85 87 18 16 25 94 18 22 16 92 32 28 88 89 92 90 90 23 90 82 72 16 20 89 24 25 94 92 92 87 93 93 24 18 92 90 22 22 20 21 18 22 91 92
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1082953765 0NEVADA 20001ENSIGN 96 92 86 84 86 90 83 26 30 16 21 90 84 17 22 21 26 18 22 91 86 15 18 89 87 14 85 30 86 88 14 87 86 88 89 42 32 75 73 17 14 15 12 18 16 19 84 86 89 87 86 36 88 86 49 100 21 88 88 17 16 22 87 17 20 13 86 27 23 81 83 88 92 86 21 91 78 67 17 19 89 20 21 87 87 89 86 86 87 21 17 88 85 20 20 18 19 20 20 87 89
1081505465 0NEVADA 10001REID 14 20 25 27 25 17 28 86 82 87 84 19 28 87 84 86 80 85 86 22 27 87 85 21 22 87 24 79 24 25 89 24 25 22 23 69 82 35 39 90 89 86 89 89 87 88 28 24 22 25 25 78 23 25 67 21 100 23 19 88 88 85 24 85 87 90 26 83 89 27 26 21 18 30 86 20 33 39 86 83 24 91 91 24 23 20 25 23 23 82 89 23 24 86 88 85 89 84 87 19 19
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1081491412 0NEW JER 10001LAUTENBERG 8 12 17 20 18 12 25 80 77 94 89 12 21 90 87 87 80 89 85 14 17 92 87 12 13 91 19 78 16 16 89 16 16 14 15 61 76 31 34 90 93 94 92 90 92 86 20 16 14 17 16 72 14 17 58 16 88 18 14 96 100 86 16 91 91 90 17 79 82 23 19 13 11 22 90 14 28 38 93 87 16 86 85 17 16 14 19 17 16 84 90 17 21 88 90 85 88 85 86 12 12
1081491266 0NEW MEX 10001BINGAMAN 14 19 24 27 24 18 29 82 79 87 85 20 27 87 88 85 81 86 85 21 25 86 85 20 22 87 25 80 25 25 85 23 24 22 22 68 80 38 40 88 87 86 89 87 86 84 27 24 23 25 25 74 22 25 63 22 85 24 21 87 86 100 23 87 89 85 23 84 85 30 26 21 19 29 85 21 34 44 86 82 23 86 83 24 23 21 25 24 24 80 86 24 28 87 89 81 85 83 84 21 20
1081410366 0NEW MEX 20001DOMENICI 93 90 92 92 94 88 77 30 34 16 23 90 90 20 23 23 30 15 26 93 90 17 22 93 93 17 89 33 92 94 18 93 94 94 95 49 36 79 75 20 17 17 12 20 17 22 90 95 92 93 94 40 95 92 56 87 24 87 86 18 16 23 100 19 22 18 93 30 28 88 88 93 89 90 22 90 81 71 16 21 89 23 26 95 93 93 90 93 94 25 17 91 91 22 21 20 20 18 22 91 93
1084010513 0NEW YOR 10001CLINTON 10 14 19 21 19 12 25 81 79 93 91 15 24 91 88 86 80 90 88 15 21 91 88 13 15 92 19 80 18 19 91 17 18 16 16 63 79 34 35 92 93 92 94 92 92 88 22 18 17 19 18 72 16 19 60 17 85 20 16 91 91 87 19 100 93 91 18 81 84 25 21 14 12 24 90 15 31 39 94 85 18 88 87 18 17 16 21 19 18 83 91 19 23 91 92 86 89 85 88 15 14
1081485813 0NEW YOR 10001SCHUMER 13 17 22 24 22 15 27 82 82 93 90 17 27 88 89 86 81 88 88 18 23 88 89 17 19 90 22 82 20 22 87 21 22 19 19 66 80 37 39 91 89 90 93 91 88 87 25 20 20 22 22 76 19 21 63 20 87 22 18 91 91 89 22 93 100 90 21 82 86 28 24 17 15 27 91 18 34 41 91 85 20 88 86 21 19 18 24 22 21 81 91 22 26 92 93 84 89 84 88 17 17
1084990247 0NORTH C 10001EDWARDS 4 10 17 19 19 10 24 86 84 92 88 12 23 92 92 87 83 91 87 16 21 91 92 14 15 93 17 83 17 15 92 17 17 14 14 61 79 30 33 93 95 91 97 93 93 89 19 17 15 16 16 72 16 18 59 13 90 16 13 90 90 85 18 91 90 100 16 87 90 22 20 14 11 20 88 11 28 38 92 85 18 93 93 16 17 14 16 16 17 81 91 16 17 88 90 89 93 89 92 12 10
1084030347 0NORTH C 20001DOLE 93 91 92 90 90 88 78 31 35 16 23 90 88 20 26 24 31 16 26 93 91 18 21 91 92 18 89 31 91 93 18 92 92 95 93 47 36 79 77 21 16 16 12 21 18 24 91 92 90 94 92 39 93 89 54 86 26 85 86 19 17 23 93 18 21 16 100 29 27 88 88 92 88 91 24 90 80 71 17 21 90 23 25 92 91 92 88 92 93 24 19 91 89 23 23 20 22 19 22 90 90
1081550236 0NORTH D 10001CONRAD 24 25 31 33 32 23 30 81 81 80 78 27 35 82 81 81 82 82 79 28 33 81 80 28 29 82 30 80 31 31 82 30 31 29 29 67 79 37 41 83 82 80 88 84 82 81 32 31 29 32 32 75 30 31 67 27 83 27 24 81 79 84 30 81 82 87 29 100 91 34 32 28 24 34 80 26 37 44 80 76 28 86 85 30 30 27 29 31 30 76 81 30 32 80 81 80 83 80 84 26 26
1081481236 0NORTH D 10001DORGAN 20 22 28 30 29 19 27 85 85 84 82 23 31 85 82 85 83 83 83 25 30 84 84 25 26 85 25 82 27 28 87 27 28 25 25 72 83 37 40 88 86 84 88 88 85 86 31 28 26 28 28 78 26 28 69 23 89 24 21 84 82 85 28 84 86 90 27 91 100 30 29 25 20 33 84 22 35 39 85 81 26 90 91 27 26 23 27 28 27 80 85 26 27 84 85 85 88 83 88 22 22
1081502024 0OHIO 20001DEWINE 92 83 86 87 87 80 77 34 37 23 29 82 84 27 32 31 38 24 31 87 86 24 27 85 86 25 87 37 88 89 25 87 88 86 87 50 39 79 75 28 24 23 19 27 26 27 88 87 85 88 88 41 86 85 55 81 27 81 80 25 23 30 88 25 28 22 88 34 30 100 88 86 82 89 30 84 82 73 24 27 86 27 27 86 87 86 85 88 88 30 26 88 89 29 29 26 26 25 28 83 83
1084990324 0OHIO 20001VOINOVICH 87 85 87 86 87 84 78 34 36 18 25 85 83 21 29 27 34 21 28 88 86 21 24 87 88 20 87 34 89 88 20 87 88 88 89 51 37 78 76 22 19 18 17 22 21 24 88 89 87 89 89 40 87 86 54 83 26 82 84 19 19 26 88 21 24 20 88 32 29 88 100 89 85 88 25 86 80 73 18 25 87 26 26 89 91 88 84 88 89 26 21 88 86 23 24 22 24 23 24 88 85
1081542453 0OKLAHOM 20001INHOFE 93 92 91 90 91 92 78 28 31 12 18 92 87 16 21 20 28 14 22 92 90 13 17 94 94 14 90 30 90 92 15 92 92 95 94 46 32 76 74 17 13 12 12 17 14 19 88 93 93 93 92 38 93 92 51 88 21 87 90 14 13 21 93 14 17 14 92 28 25 86 89 100 93 88 19 91 78 71 13 18 90 20 22 93 92 93 88 92 93 21 15 91 88 18 19 17 18 16 18 93 94
1081490853 0OKLAHOM 20001NICKLES DO 96 94 89 85 88 94 81 24 28 10 17 94 84 13 19 17 24 13 19 92 88 11 15 93 91 10 88 26 88 90 12 89 90 92 92 42 29 74 71 14 9 11 7 13 12 16 85 90 92 89 90 33 90 89 47 92 18 87 91 13 11 19 89 12 15 11 88 24 20 82 85 93 100 85 17 93 77 67 12 16 91 17 18 91 90 92 86 89 91 18 13 90 87 16 16 14 14 15 15 93 94
1084970572 0OREGON 20001SMITH GORD 93 87 90 90 90 84 79 36 39 22 29 87 88 25 31 29 35 22 30 90 90 22 26 88 89 23 87 36 90 92 24 89 91 90 90 51 40 83 78 26 22 22 18 26 23 30 91 90 87 90 90 44 90 87 59 86 30 85 83 24 22 29 90 24 27 20 91 34 33 89 88 88 85 100 30 86 81 74 22 26 87 29 30 89 90 88 85 90 91 31 24 90 90 29 28 24 26 24 27 86 87
1081487172 0OREGON 10001WYDEN 10 19 25 27 23 17 28 83 84 91 92 20 28 87 87 86 81 85 86 21 25 87 86 20 21 86 24 80 22 23 88 23 24 21 21 65 81 38 41 91 88 89 91 90 88 87 27 22 21 24 23 77 20 22 62 21 86 22 20 91 90 85 22 90 91 88 24 80 84 30 25 19 17 30 100 20 35 42 90 85 23 87 87 23 21 19 25 23 23 82 90 23 27 90 92 83 87 84 89 18 18
1082914114 0PENNSYL 20001SANTORUM 98 93 90 87 88 92 81 27 30 13 20 92 84 15 21 19 27 15 21 92 88 13 17 92 91 13 87 29 90 91 14 89 90 91 92 44 32 76 73 16 11 13 8 15 14 17 88 90 90 89 90 36 90 88 49 91 20 88 91 15 14 21 90 15 18 11 90 26 22 84 86 91 93 86 20 100 81 67 14 19 91 19 19 90 90 92 89 91 90 21 15 91 89 18 18 16 17 17 18 91 92
1081491014 0PENNSYL 20001SPECTER 83 78 80 83 81 77 72 39 43 29 35 78 81 30 35 33 39 30 36 81 79 28 31 79 80 28 77 40 79 81 27 81 81 79 80 53 45 79 78 32 28 29 18 31 28 31 81 81 79 81 82 47 80 78 59 78 33 79 77 29 28 34 81 31 34 28 80 37 35 82 80 78 77 81 35 81 100 68 29 33 80 32 35 79 80 79 81 83 82 33 31 82 82 31 33 30 31 30 32 79 77
10849905 5 0RHODE I 20001CHAFEE 59 67 69 72 73 67 69 41 43 36 43 68 69 42 49 44 48 39 43 70 69 39 41 69 70 39 72 43 73 72 38 70 72 70 71 47 43 75 76 41 39 39 46 40 39 39 71 71 70 72 72 47 71 71 49 67 39 71 68 39 38 44 71 39 41 38 71 44 39 73 73 71 67 74 42 67 68 100 38 37 69 39 38 72 72 70 68 71 71 44 39 69 74 41 41 38 38 38 40 69 68
10829142 5 0RHODE I 10001REED 7 13 18 19 17 12 25 79 78 93 88 13 21 91 86 88 81 89 86 14 18 93 89 13 14 92 17 79 16 17 92 16 16 14 14 62 77 32 34 91 94 95 93 91 92 86 20 16 15 17 16 72 14 18 58 17 86 19 14 92 93 86 16 94 91 92 17 80 85 24 18 13 12 22 90 14 29 38 100 86 16 87 87 16 15 14 18 17 15 83 93 17 22 90 89 88 90 86 89 12 12
1081120448 0SOUTH C 10001HOLLINGS 16 18 23 25 23 16 27 79 77 86 83 17 26 84 80 84 78 87 83 19 23 87 86 18 19 85 22 76 20 20 87 20 21 18 19 67 80 34 34 85 87 86 85 83 85 83 24 21 20 21 20 71 19 21 61 19 83 23 19 86 87 82 21 85 85 85 21 76 81 27 25 18 16 26 85 19 33 37 86 100 22 83 82 21 21 18 23 22 21 79 86 22 25 84 86 84 84 80 83 18 16
1082956648 0SOUTH C 20001GRAHAM 90 91 91 87 88 88 81 30 33 16 22 90 85 18 25 23 29 18 24 94 89 17 20 91 92 15 87 31 89 90 17 90 90 91 92 46 34 77 72 19 15 16 13 19 17 22 88 89 91 90 89 38 90 90 52 89 24 85 89 17 16 23 89 18 20 18 90 28 26 86 87 90 91 87 23 91 80 69 16 22 100 22 24 90 91 90 87 89 90 23 18 90 86 20 20 20 21 22 22 90 90
1081461737 0SOUTH D 10001DASCHLE 14 18 23 26 25 15 26 89 86 88 86 19 28 87 86 85 81 86 87 21 26 87 86 20 21 90 23 81 24 24 89 23 24 21 22 70 83 36 39 90 90 87 91 91 89 90 28 24 22 25 24 80 22 24 67 20 91 21 18 88 86 86 23 88 88 93 23 86 90 27 26 20 17 29 87 19 32 39 87 83 22 100 95 23 23 19 24 23 23 80 88 22 24 87 89 83 90 84 89 18 17
1081542537 0SOUTH D 10001JOHNSON 14 19 25 28 26 17 25 88 86 87 85 21 30 86 85 85 79 83 86 23 28 86 86 23 24 87 24 81 25 25 89 25 25 23 23 70 83 35 40 89 89 86 91 90 87 90 28 25 23 26 25 83 24 26 68 21 91 21 18 86 85 83 26 87 86 93 25 85 91 27 26 22 18 30 87 19 35 38 87 82 24 95 100 24 24 21 25 25 25 79 87 24 24 86 87 84 89 84 90 20 20
1084950254 0TENNESS 20001FRIST 95 91 92 91 94 89 79 32 35 16 23 91 89 20 25 22 31 16 26 94 91 17 21 93 92 18 89 33 92 94 17 92 94 95 96 49 36 78 75 20 16 16 11 20 18 22 89 95 91 93 94 39 94 91 54 87 24 87 87 18 17 24 95 18 21 16 92 30 27 86 89 93 91 89 23 90 79 72 16 21 90 23 24 100 92 93 88 93 94 24 17 91 90 22 22 20 21 18 21 91 92
1084030454 0TENNESS 20001ALEXANDER 97 89 91 89 92 89 80 31 33 14 22 90 87 18 24 24 31 18 24 94 92 17 20 93 92 17 89 32 93 93 18 93 93 92 93 47 34 78 76 18 15 15 12 19 17 21 91 93 92 92 92 38 92 92 53 87 23 86 88 16 16 23 93 17 19 17 91 30 26 87 91 92 90 90 21 90 80 72 15 21 91 23 24 92 100 92 88 93 93 25 16 91 89 21 20 18 20 20 21 92 90
1084030549 0TEXAS 20001CORNYN 95 92 90 90 92 92 79 28 31 13 21 93 88 16 23 21 27 16 23 93 91 14 18 93 93 14 89 29 92 94 14 92 93 95 94 45 32 76 74 17 13 13 10 17 16 18 89 94 93 92 92 37 94 91 50 89 20 86 89 16 14 21 93 16 18 14 92 27 23 86 88 93 92 88 19 92 79 70 14 18 90 19 21 93 92 100 89 93 94 22 15 93 90 18 18 17 18 16 19 93 94
1084930649 0TEXAS 20001HUTCHISON 93 88 86 88 89 86 78 31 34 18 26 87 87 22 25 25 30 19 27 89 87 18 23 88 87 20 84 34 87 89 19 90 89 89 89 48 36 77 74 22 18 19 12 22 20 23 86 89 87 89 87 41 88 87 54 86 25 84 86 21 19 25 90 21 24 16 88 29 27 85 84 88 86 85 25 89 81 68 18 23 87 24 25 88 88 89 100 90 89 26 20 89 88 23 24 21 22 22 24 88 87
1084930767 0UTAH 20001BENNETT 95 89 93 92 94 89 78 30 33 16 24 91 90 19 23 22 29 17 25 94 92 17 22 93 93 18 88 31 92 93 18 93 94 93 94 48 35 79 74 20 16 16 10 19 16 22 91 95 90 92 93 39 93 91 54 86 23 87 88 18 17 24 93 19 22 16 92 31 28 88 88 92 89 90 23 91 83 71 17 22 89 23 25 93 93 93 90 100 97 24 18 94 92 21 22 19 20 18 21 91 92
1081450367 0UTAH 20001HATCH 97 90 94 92 93 90 78 31 33 16 23 91 89 19 25 22 29 16 25 94 91 17 21 94 94 17 89 32 92 93 17 93 94 95 95 48 35 79 75 20 15 15 13 19 17 22 91 95 93 93 93 39 94 91 54 87 23 86 87 18 16 24 94 18 21 17 93 30 27 88 89 93 91 91 23 90 82 71 15 21 90 23 25 94 93 94 89 97 100 24 18 94 90 22 22 19 20 18 21 91 92
10894240 6 0VERMONT 32801JEFFORDS 18 19 25 27 25 19 29 76 74 83 81 20 27 83 85 83 80 84 79 22 25 84 80 21 23 84 26 74 26 25 84 25 25 22 23 67 75 38 40 83 85 85 89 83 83 80 29 24 23 25 24 76 23 27 62 21 82 24 21 83 84 80 25 83 81 81 24 76 80 30 26 21 18 31 82 21 33 44 83 79 23 80 79 24 25 22 26 24 24 100 84 24 28 83 82 81 82 80 82 21 20
10814307 6 0VERMONT 10001LEAHY 10 15 19 21 18 13 26 80 79 93 87 15 24 90 86 88 82 88 85 15 20 90 89 13 15 90 19 79 18 19 91 18 18 16 16 63 79 33 36 90 91 91 95 92 90 87 22 17 16 19 18 74 15 19 60 17 89 20 15 91 90 86 17 91 91 91 19 81 85 26 21 15 13 24 90 15 31 39 93 86 18 88 87 17 16 15 20 18 18 84 100 19 23 90 91 88 89 87 89 14 14
1082914840 0VIRGINI 20001ALLEN 95 90 92 89 91 89 78 31 33 17 24 91 88 19 26 23 29 18 24 93 90 17 22 91 92 17 87 30 91 92 17 90 91 93 94 47 35 78 74 20 15 17 10 19 17 21 91 92 92 92 92 39 91 89 53 88 23 86 87 19 17 24 91 19 22 16 91 30 26 88 88 91 90 90 23 91 82 69 17 22 90 22 24 91 91 93 89 94 94 24 19 100 92 21 21 20 21 18 21 91 92
1081471240 0VIRGINI 20001WARNER 90 88 89 90 91 86 78 30 34 21 27 88 89 23 29 26 33 20 27 90 88 21 26 89 88 21 88 32 91 91 20 90 91 90 91 46 36 80 75 23 19 20 13 23 20 24 88 91 88 90 90 39 90 90 52 85 24 85 85 22 21 28 91 23 26 17 89 32 27 89 86 88 87 90 27 89 82 74 22 25 86 24 24 90 89 90 88 92 90 28 23 92 100 26 25 23 22 21 24 88 89
1083931073 0WASHING 10001CANTWELL 18 18 23 24 22 16 28 83 81 91 87 17 25 89 90 88 81 86 87 18 24 88 87 17 19 90 23 81 22 23 89 21 23 19 20 65 79 35 38 91 90 89 94 92 89 88 26 21 20 23 22 74 19 23 63 20 86 22 18 89 88 87 22 91 92 88 23 80 84 29 23 18 16 29 90 18 31 41 90 84 20 87 86 22 21 18 23 21 22 83 90 21 26 100 95 85 88 85 88 16 16
1084930873 0WASHING 10001MURRAY 13 17 22 25 22 15 26 83 81 92 89 18 26 89 90 87 81 87 88 18 24 88 88 17 19 90 23 81 21 22 89 22 22 20 20 67 80 37 38 94 90 89 96 93 90 89 26 21 20 23 22 77 20 21 65 20 88 22 18 92 90 89 21 92 93 90 23 81 85 29 24 19 16 28 92 18 33 41 89 86 20 89 87 22 20 18 24 22 22 82 91 21 25 95 100 84 88 84 88 17 17
108 136656 0WEST VI 10001BYRD ROBER 19 16 20 23 22 13 24 79 76 86 82 15 23 86 80 86 79 86 82 18 22 87 86 17 18 87 20 77 20 20 89 19 20 18 19 63 76 30 33 88 90 87 90 87 89 83 22 20 18 21 20 71 19 22 60 18 85 19 15 86 85 81 20 86 84 89 20 80 85 26 22 17 14 24 83 16 30 38 88 84 20 83 84 20 18 17 21 19 19 81 88 20 23 85 84 100 88 85 87 15 15
1081492256 0WEST VI 10001ROCKEFELLER 13 16 21 23 22 13 25 85 82 89 85 17 25 87 87 86 81 89 87 19 24 89 87 17 19 91 21 81 21 22 89 21 22 19 20 66 81 36 39 90 91 89 93 89 90 88 25 20 19 23 21 75 19 22 63 19 89 20 16 87 88 85 20 89 89 93 22 83 88 26 24 18 14 26 87 17 31 38 90 84 21 90 89 21 20 18 22 20 20 82 89 21 22 88 88 88 100 86 90 16 15
1084930925 0WISCONS 10001FEINGOLD 19 16 19 22 19 17 29 78 76 86 83 16 22 86 84 87 79 88 81 18 23 85 83 17 18 87 22 77 21 20 87 21 19 17 17 61 75 32 34 87 87 86 94 87 88 85 24 17 17 20 18 70 16 21 58 20 84 19 19 86 85 83 18 85 84 89 19 80 83 25 23 16 15 24 84 17 30 38 86 80 22 84 84 18 20 16 22 18 18 80 87 18 21 85 84 85 86 100 90 16 15
1081570325 0WISCONS 10001KOHL 17 17 21 25 23 16 27 83 83 88 88 18 27 89 88 89 83 91 86 21 25 89 87 19 19 89 22 82 23 22 90 23 22 19 21 65 80 34 38 91 89 87 93 91 90 88 26 22 20 22 22 76 20 24 64 20 87 22 18 88 86 84 22 88 88 92 22 84 88 28 24 18 15 27 89 18 32 40 89 83 22 89 90 21 21 19 24 21 21 82 89 21 24 88 88 87 90 90 100 16 16
1084970668 0WYOMING 20001ENZI 93 92 90 87 89 91 78 26 29 11 19 94 86 14 20 19 27 14 20 92 90 13 17 93 92 12 87 28 89 91 12 91 91 94 92 44 31 76 72 15 11 13 7 14 13 17 86 91 91 90 91 35 92 89 49 87 19 87 90 13 12 21 91 15 17 12 90 26 22 83 88 93 93 86 18 91 79 69 12 18 90 18 20 91 92 93 88 91 91 21 14 91 88 16 17 15 16 16 16 100 96
1081563368 0WYOMING 20001THOMAS 95 94 91 89 90 93 78 24 28 11 18 94 86 14 19 17 24 12 20 92 89 11 16 94 93 11 88 26 89 92 13 90 91 95 93 43 29 75 72 14 10 12 8 14 11 17 85 92 92 90 92 36 93 90 48 89 19 87 90 14 12 20 93 14 17 10 90 26 22 83 85 94 94 87 18 92 77 68 12 16 90 17 20 92 90 94 87 92 92 20 14 92 89 16 17 15 15 15 16 96 100
*************HOUSYM3.DAT***************
SEN108KH.ORD The SYMSTRT3.DAT file is
SEN108.DAT echoed back here
(36A1,1600I1)
675 36 20 0.025
NUMBER OF RECORDS READ 101 Tells you the number of Legislators
COUNTS 0 - 9 0 42684 0 0 0 0 22198 0 0 3293 Counts of Roll Call Choices
ROLL-CALLS READ= 675 NUMBER REJECTED= 156 NUMBER ACCEPTED= 519 CUTOFF= 0.025 How Many Roll Calls Included
LEGISLATORS READ= 101 NUMBER REJECTED= 0 NUMBER ACCEPTED= 101 CUTOFF= 20 How Many Legislators Included
DISTRIBUTION OF SCALABLE ROLL CALLS
1 50 - 55 224 0.432
2 56 - 60 118 0.227 This Shows You the distribution of
3 61 - 65 40 0.077 Roll Call Margins
4 66 - 70 34 0.066
5 71 - 75 23 0.044
6 76 - 80 16 0.031
7 81 - 85 17 0.033
8 86 - 90 14 0.027
9 91 - 95 12 0.023
10 96 - 99.5 21 0.040
AVERAGE MAJORITY MARGIN= 30747 50091 0.61382 The Average Majority Margin is about 61-39
COUNTS 0 - 9 2328 27939 0 0 0 0 22152 0 0 0 Counts After Recoding
MISSING ELEMENTS 101 0 0.0000 Tells you the Number and Percentage of Missing Agreement Scores
ERROR PARAMETER EIGENVALUE-EIGENVECTOR ROUTINE= 0 A flag -- = 0 if Decomposition is OK
EIGENVALUES OF DECOMPOSITION
1 14.53051 0.99869 15.21368 211.69098 211.69099
2 0.37084 0.02549 Eigenvalue, Normalized Eigenvalue
3 0.26716 0.01836 15.21368 = Sum of the Squared Diagonal Entries
4 0.17385 0.01195 in the Double-Centered Matrix
5 0.15243 0.01048 211.6908 = Sum of the Squared Elements in D-C matrix
6 0.11539 0.00793 211.6908 = Sum of the Squared Eigenvalues
7 0.09274 0.00637
8 0.08662 0.00595
9 0.08259 0.00568
10 0.07744 0.00532
11 0.06971 0.00479
12 0.06304 0.00433
13 0.05943 0.00408
14 0.05774 0.00397
15 0.05408 0.00372
16 0.04671 0.00321
17 0.04369 0.00300
18 0.04149 0.00285
19 0.03851 0.00265
20 0.03785 0.00260
etc etc etc
99 -0.11745 -0.00807
100 -0.23012 -0.01582
101 -0.31978 -0.02198
20.10.47.89.
ELAPSED TIME OF JOB 20.10.48.04.
- Turn in a copy of the HOUSYM3.DAT output file.
- Turn in a plot of the eigenvalues. Use R to do the plot.
- Use Epsilon to enter the following
commands on top of your agreement score output file:
TORSCA PRE-ITERATIONS=3 DIMMAX=3,DIMMIN=1 COORDINATES=ROTATE ITERATIONS=50 REGRESSION=DESCENDING DATA,LOWERHALFMATRIX,DIAGONAL=PRESENT,CUTOFF=.01 108TH U.S. SENATE AGREEMENT SCORES 101 1 1 (36X,101F4.0) *********agreement score file********* COMPUTE STOP
Be sure to put the COMPUTE and STOP lines on the bottom of the agreement score file.
Run KYST on this file and report the STRESS values for one, two, and three dimensions.
- Make a two-dimensional plot of the Senators and President Bush using R.
Check out the Double-Centering Program posted on my book page:
Spatial Models of Parliamentary Voting: Chapter 1
You can cannibalize the R code to do this plot. Label a few of the main Senators along with President Bush (be creative!!).