These r-scripts replicate the empirical analysis presented in Crombez and Høyland (2015) The Budgetary Procedure in the European Union and the Implications of the Treaty of Lisbon, European Union Politics, Vol 16(1). The script first prepares and combines the voting data on budgetary for the Council and the EP obtained from votewatch.eu. Then it runs 1 and 2 dimensional irt-models. It then makes the table that compares the fit of the one and two dimensional models, presented in table 2 in the paper, before reproducing the main results, found in figure 3 in the paper.

We first prepare the voting data from the EP. These were collected on a vote-by-vote basis from ‘votewatch.eu’.

set.seed(985236)
votes <- list.files("../EP_votes/")
votes <- votes[-length(votes)]
onevote<- list()
for (i in 1:length(votes)){
  onevote[[i]] <- cbind(i,read.csv(paste("../EP_votes/",votes[i],sep="")))
  colnames(onevote[[i]]) <- c("voteid","name","state","loyal","vote","group")
}
votes <- data.frame(do.call("rbind",onevote))
votes <- votes[,-4]
votematrix <- reshape(votes, timevar=c("voteid"),idvar=c("name","state","group"),direction="wide")

library(pscl)
## Loading required package: MASS
## Loading required package: mvtnorm
## Loading required package: coda
## Loading required package: lattice
## Loading required package: gam
## Loading required package: splines
## Loaded gam 1.09.1
## 
## Loading required package: vcd
## Loading required package: grid
## Classes and Methods for R developed in the
## 
## Political Science Computational Laboratory
## 
## Department of Political Science
## 
## Stanford University
## 
## Simon Jackman
## 
## hurdle and zeroinfl functions by Achim Zeileis
legisdata <- data.frame(with(votematrix,cbind(as.character(state),as.character(state),0,
                                              1:nrow(votematrix),as.character(group),as.character(group))))
colnames(legisdata) <- c("state","icpsrState","cd","icpsrLegis","partyName","party")
voteinfo <- read.csv("../EP_votes/VoteInfo.csv")

info <- tolower(voteinfo$Name.of.document)
legisnames <- paste(votematrix$name,votematrix$state,votematrix$group,sep=" ")
rownames(votematrix) <- legisnames
votemat <- t(votematrix[,4:ncol(votematrix)])
trim <- function (x) gsub("^\\s+|\\s+$", "", x)
voteinfo$Name.of.document <- trim(voteinfo$Name.of.document)
votematInfo <- cbind(voteinfo[,1:2],votemat)

For the Council, ‘votewatch.eu’ gave us the full voting matrix with the auxiliary information. The procedure for preparing the data is slightly different.

tmp <- file("../CouncilVotes//BudgetvotesinCouncil.csv",encoding="Latin1")
votes <- read.csv2(tmp)
C.voteinfo <- votes[,1:33]
info <- trim(C.voteinfo$EP.ref)
voting <- t(votes[,62:89])
voting[is.na(voting)] <- 1

names <- unlist(strsplit(rownames(voting),split=".1"))
rownames(voting) <- names
###################
C.voting <- t(voting)
C.voting[voteinfo$Negative==1,] <- abs(C.voting[voteinfo$Negative==1,] -1)
C.voting[C.voting>1] <- "Against"
C.voting[C.voting==1] <- "For"

We then merge the two datasets together on the basis of the vote-info.

C.vote <- cbind(C.voteinfo[,31:32],C.voting)
C.vote$EP.ref <-  gsub(" -.*","",C.vote$EP.ref)
votematInfo$Name.of.document <-  gsub(" -.*","",votematInfo$Name.of.document)
C.vote$EP.date <- as.Date(C.vote$EP.date,format="%d.%m.%y")
C.vote <- C.vote[C.vote$EP.date>"2009-12-01",]
votematInfo$Date <- as.Date(votematInfo$Date,format="%d.%m.%Y")
votematInfo <- votematInfo[votematInfo$Date>"2009-12-01",]
votematInfo <- votematInfo[-1,]
test <- merge(C.vote,votematInfo,by.x=c("EP.date","EP.ref"),by.y=c("Date","Name.of.document"),all=TRUE)
votes <- test[,3:ncol(test)]
info <- test[,1:2]
for (i in 1:ncol(votes)){
votes[,i] <- ifelse(votes[,i]=="For",1,ifelse(votes[,i]=="Against",0,9))
}

legdata <- cbind(names,names,0,0,"council","council")
colnames(legdata) <- names(legisdata)
rownames(legdata) <- names
rownames(legisdata) <- legisnames
legisdata <- rbind(legdata,legisdata)
legisnames <- t(rownames(legisdata))
vot <- rollcall(t(votes),
                  legis.names=legisnames,
                  legis.data=legisdata,vote.data=info,
                  desc="EP and Council Budget votes 2009-12-01 - 2014-01-02",
                  source="votewatch.eu")

We are now ready to run the analysis. Note that we run the default number of iterations, burnin and thinning, rather than 100.000, after 10.000 burn-in with a thinning of 50 as reported in the paper. The substantive results are not affected by this change.

vot <- dropRollCall(vot,dropList=list(lop=1,legisMin=10))
out1 <- ideal(vot,d=1,store.item=TRUE)
## ideal: analysis of roll call data via Markov chain Monte Carlo methods.
## 
## Ideal Point Estimation
## 
## Number of Legislators         879 
## Number of Items           185 
## 
## 
## Starting MCMC Iterations...
## 
##   [1] -0.3642320 -1.6596150 -0.5721060  0.3793924 -0.5807004 -1.3596494
##   [7] -2.1632699 -0.8574518  0.0869559 -1.6448841 -0.3946562 -0.0780867
##  [13] -0.6734724  0.0634710 -0.9210432 -0.4299425 -1.0937631 -1.3296048
##  [19]  0.8236861  0.1084242  0.1106637  0.2968537  0.0538292 -0.0275050
##  [25] -1.0539214  0.3298937  0.9653798  0.9354770 -2.6450450  2.7115999
##  [31] -0.9875095  0.3373122 -1.8801497  0.2617330 -0.8113204 -0.2514631
##  [37] -1.1863465 -0.9412912  3.4776133 -0.7497147 -2.5423988 -0.4244189
##  [43] -0.9844908 -1.3803041 -1.8198234 -1.7015857 -1.1320905 -0.9687494
##  [49] -1.1800381  1.4544942  1.3351144 -1.7156196 -1.9911277 -0.9914184
##  [55]  0.2582349 -2.6793684 -0.7170321 -0.1939483  0.4838451 -0.5718505
##  [61] -1.0926475  0.5119636 -0.9479288 -3.0209655 -0.9444045 -1.4068799
##  [67] -2.1573770 -0.8302388  2.3920195 -0.8658074 -0.3939087 -0.0948644
##  [73]  0.3687565  0.7032196 -0.8286220  0.1944311  0.1526274 -0.1586053
##  [79] -2.4600748 -0.3687480 -0.2471308 -1.0866799  0.3513106  1.1597121
##  [85] -0.2942784  0.7100468  0.4803900  0.5448712 -0.9978076  2.3876847
##  [91] -0.3865325  1.3163233  0.0946197  3.3125444  0.4902374 -0.3700771
##  [97] -1.6912306  0.2875072 -0.0635669 -0.2255890 -0.3363105  1.4563720
## [103]  0.4917010 -0.3072757 -1.6750197  1.6207581 -1.7300531  0.5974775
## [109]  2.7448135 -1.5172217 -0.6956543 -0.2527784 -0.4167399 -1.8485868
## [115]  0.3799989 -2.4256831  0.2846599 -0.6874218 -0.1850644  1.2007839
## [121] -0.2402414  1.4716019 -0.1581209  1.4067740 -0.1227922  0.4424118
## [127]  0.4815316 -1.7201892 -1.1548577 -2.6900679  0.4087129 -0.0345586
## [133] -0.2152144 -0.1347237 -0.0001574 -1.1313514 -1.7593580 -0.6402500
## [139]  1.4052695 -0.7123764  0.5389625  0.2704876  0.7962497  3.1598441
## [145] -1.9456010 -0.0039114  0.4617250 -0.5026940  2.7001557 -1.7198635
## [151]  0.1237479  0.3839100 -0.0744613 -0.8944665 -0.3022053 -0.1638091
## [157]  0.1713460 -0.6682300 -1.1887778 -0.4157568 -0.4564381 -1.5656803
## [163]  1.0784515  1.0899465 -2.1160739  1.3439543 -1.3314709 -0.4700733
## [169]  2.9318498 -0.9639871 -0.8352391 -0.4442857 -0.0405061 -0.7587712
## [175] -0.9825014 -0.5836435 -0.1569397 -2.0484665 -2.2574599 -1.1015227
## [181] -0.5622537  0.2430259 -1.0885361 -0.5054097 -1.1084102  1.2927676
## [187]  2.2395747 -1.3826055 -0.4042134 -0.3439143 -1.1044247  0.3413138
## [193] -0.9316795 -0.9992530 -0.3758078 -1.3383974 -0.4716735  0.6726317
## [199]  0.3033183 -0.0608205 -0.5407229  0.9833673 -1.6292092 -0.1766598
## [205]  0.2817035  1.3709773  0.3346572 -0.6230499  0.2535978 -0.8083266
## [211] -0.8900471  0.3825684  1.4313066 -0.6492162 -1.5510345  2.5836145
## [217] -1.5312540 -0.3568669 -2.6574664 -0.0401897  0.6722465 -0.9190693
## [223]  0.7048472 -1.2590451  0.2778687  0.2950323 -0.1792572 -1.9492409
## [229] -0.7718158  0.5289707  1.7149721  1.5286741  1.4673376 -1.1004548
## [235] -0.2234134 -0.5625606 -0.4459400 -1.6797810 -1.5551417 -2.0937699
## [241] -0.1787706 -0.1742529 -0.5616412  0.1427676 -1.7983208 -2.0392277
## [247] -0.7732926 -0.7190898 -0.0167454 -1.4520332 -0.7563315  0.2454802
## [253] -0.8760877  1.4055216 -1.5322054 -1.9365022  0.1468575  0.0948498
## [259] -0.7762049  0.7198579 -2.8877903 -1.1355478 -1.1739410 -0.8499288
## [265]  0.1163439 -0.7641036  1.8120153 -0.9583902 -1.6239912 -0.7141001
## [271] -1.2783391 -0.3556245 -0.5113202  0.2760733  1.0848584 -1.1279865
## [277] -0.7338533 -1.8981300 -0.7882207 -1.1525465 -0.9316066 -1.4334124
## [283] -0.2857363 -0.5495614  0.6283190  0.0734817  0.2601513 -0.5500048
## [289] -0.6874318  1.5114295  1.4705430 -1.3560035  0.2962551  0.2560445
## [295]  0.4347513  0.4149448 -0.4376968  0.2529891  1.9062036  0.2317508
## [301] -1.1204670  0.3092416 -0.7183040 -1.0110603  0.7507917  0.3493042
## [307] -0.8275306  0.7169801 -1.2763829  0.5179447  0.5866971  0.4677232
## [313]  0.4505512 -0.9384283  0.3574851  0.3806941  0.2953657  1.0414350
## [319]  0.4429700 -1.7498429 -0.4167678  0.4164778 -0.9962018 -0.2397383
## [325] -0.5987824 -0.1030603 -0.4537980 -1.0749756 -0.1146611 -0.0088053
## [331]  1.4263811 -0.1803631  0.4294078 -0.5546450 -1.1594088 -1.3106423
## [337] -1.2206304 -1.1046373  0.3572346  0.7281671 -1.0874579  0.2864265
## [343]  0.1721670 -1.4212342  0.0281631  0.0348031  0.1810135 -0.8476687
## [349] -1.0458152 -0.1134616 -1.3138280 -1.6590689 -0.8981183 -0.5996102
## [355]  1.5296460  0.8597324 -0.9996891 -0.8297548  1.4656868 -0.4071596
## [361] -0.2752053 -0.0636489  0.1345999 -0.6048613  0.2736107 -0.1115895
## [367] -1.1612301  0.2993050 -2.0167442  1.2911269 -0.8584763 -0.7573018
## [373]  0.2697753 -1.6110116 -1.1650821  0.1047611 -0.6493644 -0.4798826
## [379] -0.8199904 -0.8833974 -1.7410740  1.1521922 -0.1793932  1.2827436
## [385] -0.1737955 -1.0723053 -1.7523489 -1.2640762 -1.1217068 -0.5932226
## [391]  1.0448888 -0.8367709 -1.1559522 -0.7610842 -0.3632119  0.4567107
## [397]  0.1316189 -1.3010636 -0.0942568 -0.6145385 -0.5423726 -0.0335380
## [403] -0.1268748 -1.4526290  0.6023640  0.7109996  0.7377593 -0.7321473
## [409]  1.0878326 -1.2368697  0.2837032 -0.8368238  0.0839287 -0.5728336
## [415]  0.1603849 -0.6293840  0.6230073 -0.3027153  0.3285442 -2.0966008
## [421]  0.0340151  0.2237402 -0.2930814 -0.4892319  0.1937764  0.0975513
## [427] -0.1955051 -2.3685765 -1.1847031  0.5851068  0.6023289 -0.1888583
## [433] -1.2585683  1.2916838  0.2188149 -2.0067427 -0.4844112 -0.2403877
## [439]  0.5037012  0.7224765 -0.4089651 -1.5656230 -1.2578911 -1.9330117
## [445] -0.5234988  0.3868022  0.1061997 -0.8138886 -1.0464112 -1.2162577
## [451] -0.0949880 -1.8293141 -1.1764484 -1.6472696  0.0564199  0.5670769
## [457]  0.4062688  1.4440143 -1.0817062  0.9684160 -0.9587943 -1.6769340
## [463] -1.7223433 -0.3957944  1.7321791  0.5882245 -0.4571636  1.1294059
## [469] -1.0376233  0.0316343 -0.6274894  0.0348935 -0.9235639  0.4419697
## [475] -0.6646889  0.5797859 -0.4126053 -2.2773820  0.5021784 -0.4432746
## [481] -1.5380702 -1.9745438  1.1932617 -0.2255803 -1.7399277  0.6941714
## [487] -1.1994617  3.0829412 -0.1989626 -0.4146221 -0.3106461 -0.7941169
## [493] -0.6657979  1.3739442 -0.4671111 -0.0536425 -1.4880129  0.1363286
## [499] -0.4161385  2.8179910  0.7179837 -1.6227053 -0.0288451 -0.6536486
## [505] -1.1441236 -0.3873047  1.4011918 -0.1934103 -0.8388497 -0.1732561
## [511] -1.7810997  0.1986544 -1.0187557 -1.0516947 -1.6654193 -0.6897126
## [517] -0.3089365 -1.1524806 -1.0236494 -0.9389293 -0.7266208 -1.1291018
## [523] -0.4684440 -0.1914217  0.0009831 -0.1455078  0.8280282 -1.5687874
## [529] -0.2133394 -0.6609602 -0.5812398 -1.2195938  1.0703411 -0.6901484
## [535] -1.9082108 -1.0000220 -1.0697854 -1.6002550 -0.7687949  0.2645276
## [541]  1.0539905 -0.9268761 -0.3492042 -0.6736900 -0.1149330 -0.3923079
## [547]  0.5949328 -2.3180193 -1.1366302 -2.0983147 -0.4216167  0.3196281
## [553] -0.5152012 -0.8558704 -0.2625451 -1.0064916  0.2058565 -1.2095592
## [559] -0.2794165 -0.9072588 -0.8761394 -0.7034733 -1.6489200  0.0702129
## [565] -1.1157007 -1.1788935 -0.0814506 -0.0984654 -0.1751092 -0.6621447
## [571]  0.2873228 -0.8173113  2.0552665  0.5159926 -1.1181820 -2.6278740
## [577]  0.5258244 -1.2878916  0.1637275  0.0134797 -0.4323736  0.6593103
## [583] -0.1450726  0.2563143 -0.9321283  0.0543356 -0.2780720 -0.8142492
## [589] -2.0692093 -0.9185409 -1.2696789 -0.3744182  0.4435251  1.3631433
## [595] -0.0125054  0.4597486  0.0597549 -1.0272978  0.5197407  0.2818935
## [601] -1.6632296  0.2027732 -0.6921330 -0.5070629 -0.9193835  0.5302872
## [607] -1.3194005 -1.1175453 -0.9163923 -0.6193670 -0.4204217 -0.4669054
## [613] -0.3365462 -1.1747471 -1.7363405  0.5358033 -1.3644038  0.0861467
## [619]  0.5099927 -1.1076376 -0.1309052  0.2729938 -0.4668372  1.4765440
## [625] -0.9470489  0.0264107 -1.8937362 -0.1276568  0.4578471  0.3347060
## [631] -0.5463529 -1.3009643 -0.2890095  1.3456321  0.5228956  1.4274086
## [637] -0.6923078  0.6141265 -0.0738777 -1.0360395  1.4695514 -1.3763433
## [643]  1.3267253 -1.0109856 -0.6335568  0.4562209  0.7817501  1.3744069
## [649] -1.8416081  0.6647220  1.1922191 -0.8019182 -0.8830907 -0.3805338
## [655] -0.4767581  0.6070099 -0.4848241  0.2544460  1.3751543 -1.3453049
## [661]  0.3709770 -0.8975446  0.3178042 -0.5029015 -0.7830992 -0.2365802
## [667] -1.3486686  0.0870059  0.0133855 -0.5479536 -1.4676759 -0.5131706
## [673] -1.6855323  0.9988095  0.7050607  1.2423254 -0.9334600  0.3187796
## [679] -0.7026082  0.5445590 -0.5634804  0.1541324 -1.8059131  0.4259529
## [685] -0.1297526 -0.1544785 -1.7900823 -0.7414421 -0.2928908 -1.6896614
## [691]  0.3304681 -1.7790191 -1.9445372 -2.3003954  0.2536445 -1.8016895
## [697] -0.6993627 -1.3656301  1.3327040  0.7321615 -0.0754986  0.4295662
## [703] -0.7075866  0.8477292 -0.9804555 -2.1854812 -0.9249252 -2.2596996
## [709] -0.4624974  1.1495234 -1.4424017  1.2362303  0.0284229 -0.6061061
## [715]  0.1305430 -0.3715512 -0.6556037 -1.4180509 -0.5896349 -0.6466061
## [721] -0.8763000 -0.9975650  0.6276325  0.2419409 -0.7650024 -0.3535613
## [727] -0.0964860  0.4736832  0.3334469  0.2318685 -0.9982112  0.9969201
## [733] -1.8035007  0.8970239  1.4648288 -0.6117641  1.2645475 -0.7176880
## [739] -0.1885729 -0.8668287 -0.5292247 -1.1184708  0.4613412 -0.3182144
## [745]  0.2303218  1.0317029 -1.5037216 -1.0261965 -1.0841096  1.1727209
## [751] -0.5436735  1.3344269 -0.9573658 -1.8945327 -0.6884538 -1.3423808
## [757]  0.4205627 -0.6183576  0.6838941 -0.6999640 -0.0076552  2.0302662
## [763] -1.1331545 -0.1072513 -1.2711931  0.7049780  0.3808343 -0.4162304
## [769]  1.3393892 -0.6132778 -0.4007007 -0.2001446 -1.4072527 -0.5003171
## [775] -1.3868526 -0.7960424  0.5187860 -1.0825159  0.3458005 -0.2718899
## [781] -2.1250047  1.5197920  0.3899860 -0.6160268 -1.4422107 -0.3012283
## [787]  0.1140015  2.1087009  0.5535173 -0.3047066 -0.0212461 -1.0760050
## [793] -1.1473415 -0.5971007 -1.4351437  1.4224657  0.1026115 -2.1075098
## [799] -0.5612141 -1.8599470 -0.7767781  0.1057184  0.7961060  0.0099386
## [805]  0.3871735 -2.2036259 -2.3040765  0.8100470  0.0396133  0.0481118
## [811] -1.7101279 -0.7598279  1.2411539  1.0922274  0.3224927 -2.1392633
## [817]  0.6603828  1.1309218  0.9142737  0.5422225  2.4553311 -1.0745804
## [823] -0.2371203 -1.5360132  0.5592757 -1.9604794  0.1181649 -0.4956875
## [829] -2.0347160  0.2490580 -0.5104211 -0.1435860 -1.8794568 -1.5120581
## [835] -0.2517067 -0.8276159 -1.4398713 -1.7103562 -1.2079256  1.7286780
## [841]  0.7580635 -1.3090759 -0.3919062  0.2292518  0.6442341 -1.5017422
## [847] -0.6104248  1.9410297 -1.7132736  1.4656393 -0.6866659 -1.5803598
## [853] -1.2049804  0.9311756  0.4481742 -1.4470713 -1.2806893  0.7799868
## [859] -0.5059390 -0.7333104 -0.6158752 -0.3596869 -0.9525004 -0.4819014
## [865] -1.1724653 -0.6273025 -1.2386814 -0.0263268 -1.1199656 -0.4260157
## [871]  0.9268802 -1.0355045  0.2005794 -0.0272177 -0.0122630  0.4302534
## [877]  0.3060316 -0.7001747 -0.8849964
##   [1] "Vote 1"   "Vote 2"   "Vote 3"   "Vote 4"   "Vote 5"   "Vote 6"  
##   [7] "Vote 7"   "Vote 8"   "Vote 9"   "Vote 10"  "Vote 11"  "Vote 12" 
##  [13] "Vote 13"  "Vote 14"  "Vote 15"  "Vote 16"  "Vote 17"  "Vote 18" 
##  [19] "Vote 19"  "Vote 20"  "Vote 21"  "Vote 23"  "Vote 24"  "Vote 26" 
##  [25] "Vote 27"  "Vote 28"  "Vote 29"  "Vote 30"  "Vote 31"  "Vote 32" 
##  [31] "Vote 33"  "Vote 34"  "Vote 35"  "Vote 36"  "Vote 37"  "Vote 38" 
##  [37] "Vote 39"  "Vote 40"  "Vote 41"  "Vote 42"  "Vote 44"  "Vote 45" 
##  [43] "Vote 46"  "Vote 47"  "Vote 48"  "Vote 49"  "Vote 50"  "Vote 51" 
##  [49] "Vote 52"  "Vote 53"  "Vote 54"  "Vote 55"  "Vote 56"  "Vote 57" 
##  [55] "Vote 58"  "Vote 59"  "Vote 60"  "Vote 61"  "Vote 62"  "Vote 63" 
##  [61] "Vote 64"  "Vote 65"  "Vote 66"  "Vote 68"  "Vote 69"  "Vote 70" 
##  [67] "Vote 71"  "Vote 72"  "Vote 73"  "Vote 74"  "Vote 75"  "Vote 77" 
##  [73] "Vote 78"  "Vote 79"  "Vote 80"  "Vote 82"  "Vote 83"  "Vote 84" 
##  [79] "Vote 85"  "Vote 86"  "Vote 87"  "Vote 88"  "Vote 89"  "Vote 90" 
##  [85] "Vote 91"  "Vote 92"  "Vote 93"  "Vote 94"  "Vote 95"  "Vote 96" 
##  [91] "Vote 97"  "Vote 98"  "Vote 99"  "Vote 100" "Vote 101" "Vote 102"
##  [97] "Vote 103" "Vote 104" "Vote 105" "Vote 106" "Vote 107" "Vote 108"
## [103] "Vote 109" "Vote 110" "Vote 111" "Vote 112" "Vote 113" "Vote 114"
## [109] "Vote 115" "Vote 116" "Vote 117" "Vote 118" "Vote 119" "Vote 120"
## [115] "Vote 122" "Vote 123" "Vote 124" "Vote 125" "Vote 126" "Vote 127"
## [121] "Vote 129" "Vote 131" "Vote 132" "Vote 133" "Vote 134" "Vote 135"
## [127] "Vote 136" "Vote 137" "Vote 138" "Vote 139" "Vote 140" "Vote 141"
## [133] "Vote 142" "Vote 143" "Vote 144" "Vote 145" "Vote 146" "Vote 147"
## [139] "Vote 148" "Vote 149" "Vote 150" "Vote 151" "Vote 152" "Vote 153"
## [145] "Vote 154" "Vote 155" "Vote 156" "Vote 157" "Vote 158" "Vote 159"
## [151] "Vote 160" "Vote 161" "Vote 162" "Vote 163" "Vote 164" "Vote 165"
## [157] "Vote 166" "Vote 167" "Vote 168" "Vote 169" "Vote 170" "Vote 171"
## [163] "Vote 172" "Vote 173" "Vote 174" "Vote 175" "Vote 176" "Vote 177"
## [169] "Vote 178" "Vote 179" "Vote 180" "Vote 181" "Vote 182" "Vote 183"
## [175] "Vote 184" "Vote 185" "Vote 186" "Vote 187" "Vote 188" "Vote 189"
## [181] "Vote 190" "Vote 191" "Vote 192" "Vote 193" "Vote 194"
out2 <- ideal(vot,d=2,store.item=TRUE)
## ideal: analysis of roll call data via Markov chain Monte Carlo methods.
## 
## normalize option is only meaningful when d=1
## Ideal Point Estimation
## 
## Number of Legislators         879 
## Number of Items           185 
## 
## 
## Starting MCMC Iterations...
## 
##    [1]  0.161177 -0.651390 -0.546015  0.561338 -1.999804 -0.029034
##    [7] -2.010152 -0.685226 -0.903979 -0.862093  0.122312 -1.897535
##   [13] -0.175823  0.305980  0.035230 -1.386496 -1.076372 -1.646360
##   [19]  0.768668  0.258155 -0.048213  0.685142  0.295521  0.226859
##   [25] -0.856505  0.706557  0.780355  0.947570 -1.178571  2.083715
##   [31] -0.460112 -0.736039 -0.206025 -0.589101 -0.200869 -0.146835
##   [37] -0.333248 -0.723210  3.322866 -0.153338 -0.488596 -0.770322
##   [43] -0.234086 -0.384539 -0.810154 -0.579332 -0.898941 -1.150522
##   [49] -0.553700  2.031311  1.720376 -0.243390 -0.377742 -0.109011
##   [55] -0.929625 -2.216829 -0.466171 -0.311974  0.373525  0.042933
##   [61] -0.242294  0.476280 -0.975349 -0.837731 -1.237609 -1.044890
##   [67] -1.645144 -0.637592  2.736385 -1.106662 -0.215282 -0.088502
##   [73]  0.311280  0.904184 -1.624566 -1.323785  0.094710 -0.332404
##   [79] -1.821662  0.022649 -0.163534 -0.536464 -0.931199  1.105334
##   [85]  0.062917  0.714350  0.460934  0.736319 -0.325315  2.692374
##   [91] -0.058205  1.762070 -0.043892  2.524690  0.454253 -1.064126
##   [97] -0.366617 -0.547910 -0.050690 -0.214742 -0.755617  1.712143
##  [103]  0.004619 -0.081208 -1.289452  1.985770 -1.020683  0.114970
##  [109]  2.523438 -1.453152 -0.894921 -0.591512 -0.114379  0.345076
##  [115] -0.768361 -0.097625 -0.128894 -0.039582 -0.283696  1.555100
##  [121] -0.588295  1.829549  0.179257  1.620748 -0.351186 -0.073674
##  [127] -0.173778 -0.327747 -1.416731 -0.911847  0.604453 -1.599299
##  [133] -0.108309 -0.129582 -0.079398 -0.318407 -0.355246 -0.204095
##  [139]  1.893914 -1.567966  0.652841  0.276287  0.952477  2.432423
##  [145] -0.790187 -0.298235 -0.983180 -2.504480  2.423502 -1.016796
##  [151]  0.384263 -0.581041 -0.090579 -0.141320 -0.247049 -0.510783
##  [157] -0.836553 -0.938752 -1.424858 -0.934712 -1.193397 -0.811743
##  [163]  1.173613  1.332557 -0.213691  1.472716 -1.983854 -0.284367
##  [169]  2.566996 -0.790827 -1.150675 -0.074715  0.192665 -1.284652
##  [175] -0.720338 -1.619791 -1.133518 -0.176170 -1.125030 -0.503463
##  [181] -0.900311 -0.527601 -0.317319 -0.699177 -0.357343  1.910932
##  [187]  2.050821 -3.177252 -0.164143  0.023026 -0.459784  0.046909
##  [193] -1.418769 -0.375355 -1.103253 -0.237501 -0.281320  0.789829
##  [199] -0.587669 -0.192148 -0.569367  1.252895 -0.521104  0.271553
##  [205] -0.326031  1.592512  0.285647 -1.065692  0.552608 -1.205988
##  [211] -0.464823 -0.866497  1.732875 -2.061794 -1.841553  2.738583
##  [217] -1.543771 -0.208734 -1.499819 -0.165978  0.786978 -1.139052
##  [223]  0.518721 -1.041797  0.516868 -1.022656 -0.567305 -1.155343
##  [229]  0.008591  0.559756  1.737679  1.827438  1.678417 -0.274531
##  [235]  0.190108 -0.264570 -1.169410 -0.634120 -0.938140 -2.013894
##  [241] -0.667463 -0.179729 -1.156467  0.178227 -0.736713 -0.188345
##  [247] -1.540681 -1.730119 -0.592305 -1.702758 -0.196372 -0.696294
##  [253] -0.974870  1.734761 -1.759153 -2.378289 -0.053976 -0.300256
##  [259] -0.021779  0.977248 -2.028818 -0.429043 -0.506170 -0.035110
##  [265] -0.522650 -0.498444  1.864760 -0.872521 -0.758205 -0.825426
##  [271] -0.909298 -1.199187  0.067166 -0.209515  1.066335 -0.175075
##  [277] -2.171243 -1.606785  0.052329 -0.315419 -0.761309 -1.393458
##  [283] -0.381569 -0.316045  0.593169 -0.122428  0.385195 -0.201076
##  [289] -0.302789  1.950609  2.008418 -1.398441 -0.792366 -0.743790
##  [295]  0.200509 -0.327680 -0.014474  0.458535  2.515154  0.897803
##  [301] -1.296013  0.218270 -0.191087 -0.750798  0.862886  0.148808
##  [307] -0.970340  1.006198 -0.874750  0.597374  0.471979  0.261627
##  [313]  0.446358 -0.381651 -0.011452  0.105717 -0.370692  1.172456
##  [319]  0.652223 -0.608401 -2.133345  0.539150 -0.140283 -0.283291
##  [325] -0.414020 -0.001701 -0.005241 -0.206439 -0.346975 -0.072656
##  [331]  2.833933 -0.251053 -0.928865 -0.166352 -0.229837 -1.286668
##  [337] -0.600192 -0.741804 -0.801224  0.797498 -0.369165  0.019913
##  [343] -0.048793 -0.373142 -1.778855  0.127579  0.196170 -0.823626
##  [349] -0.614423  0.017439 -0.570953 -0.663421 -0.328774 -1.940984
##  [355]  1.834612  0.710883 -1.809371 -0.888819  2.353301 -0.016970
##  [361] -1.419030 -0.236451 -0.066131 -0.634818 -1.604963 -0.539368
##  [367] -2.702703 -0.773815 -0.411807  1.689738 -0.566665 -1.296223
##  [373]  0.224342 -0.635200 -0.633971  0.012479 -0.167765 -0.619549
##  [379] -1.027009 -1.313440 -0.201372  1.094461 -2.378936  1.478502
##  [385]  0.013709 -0.454183 -0.461348 -0.315573 -0.044161 -0.252281
##  [391]  1.011045 -0.947258 -0.993864 -0.123578 -0.184818 -0.611545
##  [397] -0.850383 -1.295150 -0.454317 -1.300752 -1.392380  0.199786
##  [403]  0.266630 -0.829096  0.770032  0.642610  0.770285  0.088694
##  [409]  1.152670 -0.722178  0.407836 -0.858368 -0.829070 -1.698354
##  [415] -0.504397 -0.809552  0.727135  0.073666 -0.207874 -3.263671
##  [421]  0.231530  0.227295 -0.090883  0.091492 -0.698727  0.344682
##  [427]  0.195651 -1.703499 -1.158332  0.462411  0.649274  0.095052
##  [433] -0.587720  2.206155  0.349823 -1.763828  0.070668 -0.013468
##  [439]  0.477982  0.724346 -0.530679 -2.249470 -1.153113 -0.623589
##  [445] -0.004252  0.064321 -0.022626 -0.615990 -0.870975 -0.516114
##  [451]  0.099002 -2.611634 -0.526735 -0.433248  0.152995  0.496171
##  [457]  0.521434  1.881005 -0.494806  1.089165 -0.400639 -0.645260
##  [463] -0.942887 -0.066345  2.431627  0.599753 -0.286504  1.014702
##  [469] -0.913222 -0.206763 -1.284328 -0.210099 -1.519886  0.631477
##  [475] -1.629956  0.568211 -0.132333 -1.360514  0.244388 -0.389521
##  [481] -1.966889 -1.431323  1.400183 -1.270462 -0.460583  0.862168
##  [487] -0.298697  2.268733 -1.695991 -1.804949  0.084970 -1.171423
##  [493] -1.004279  1.670337 -0.330440 -1.006608  0.108186 -0.113928
##  [499] -0.459279  2.550358  0.931913 -0.243282 -0.040220 -0.135880
##  [505] -1.374095 -1.027285  1.671116 -0.280526 -0.341439 -0.384738
##  [511] -0.691510  0.267122 -0.217030 -0.892663 -1.400771 -0.717680
##  [517] -1.835077 -1.195335  0.045675 -1.029147 -1.468166 -0.601305
##  [523] -0.536903 -0.136817 -0.118296 -0.879397  0.950453 -0.838442
##  [529] -1.294972 -0.897722 -0.174469 -1.627525  1.095685 -1.186915
##  [535] -1.006188 -1.515380 -1.379703 -0.579237 -1.019691 -0.053263
##  [541]  1.104239  0.213334  0.188191 -1.623978 -1.953809 -0.528210
##  [547]  0.713429 -1.510392 -0.884340 -1.204862 -0.540006  0.486851
##  [553] -1.595731 -1.446844 -0.339509 -0.055270  0.071964 -0.612829
##  [559]  0.106080 -1.053746 -0.972239 -0.864009 -1.130236 -1.340752
##  [565] -1.684624 -0.815911 -0.316161  0.049054  0.034834 -0.225000
##  [571] -0.524565 -0.895673  2.256768  0.551601 -1.840914 -0.936579
##  [577]  0.488014 -0.510879 -1.606002  0.010999 -1.487813  0.702423
##  [583] -0.043871 -0.211000 -0.942775  0.131379 -0.438799 -1.206581
##  [589] -1.154847 -0.405477 -0.862975 -1.003036  0.107554  1.566005
##  [595]  0.305911 -1.146980  0.097865 -1.333993 -0.150121 -0.865276
##  [601] -0.559465 -0.742311 -0.441306 -0.623292 -0.672603  0.618966
##  [607] -0.514663 -0.660320 -1.490144 -1.136041 -1.440668 -0.002579
##  [613] -0.554430 -0.650776 -1.272153  0.471337 -0.463471 -0.062408
##  [619]  0.539257 -1.017546 -0.681649  0.105108 -1.715493  1.758941
##  [625] -1.087833  0.072752 -1.685314 -1.533061  0.586851 -0.284617
##  [631] -0.393427 -1.068611 -1.238588  1.551278  0.433620  2.095792
##  [637]  0.012537  0.609816 -0.538393 -0.549007  1.716895 -0.358619
##  [643]  1.974722 -1.567069 -1.070273  0.370190  0.764052  1.932279
##  [649] -2.086187  0.764096  1.296102 -1.998682 -2.461222  0.087564
##  [655] -0.455837  0.739009 -2.350644  0.207038  1.951480 -0.854988
##  [661] -0.086508 -0.896633 -0.928157 -0.368581 -0.615992 -0.098216
##  [667] -1.948169  0.151536  0.240695 -0.905670 -0.904345 -0.930217
##  [673] -0.588306  0.949730  0.774161  1.613438 -0.906110 -0.916212
##  [679] -0.998634  0.641351 -1.501615 -0.502527 -0.550261 -1.185261
##  [685] -0.511921 -0.596378 -1.012070 -0.078951 -0.347597 -0.524210
##  [691]  0.345027 -0.840025 -0.640423 -0.855225  0.451927 -0.850280
##  [697] -1.494708 -0.395612  1.681204  0.927295  0.196807  0.421251
##  [703] -1.488502  0.963119 -2.575802 -0.625308 -0.288901 -2.107089
##  [709] -0.671192  1.504664  0.211352  1.427235 -0.549771 -0.068740
##  [715]  0.289595  0.119720 -0.538152 -0.800684 -0.054096 -0.476111
##  [721] -1.419895 -0.695057  0.628258  0.301580 -0.777038 -0.934597
##  [727]  0.154784  0.562207  0.057327  0.481853 -0.902735  0.980820
##  [733] -0.101650  0.920096  1.505709 -1.014100  1.731285 -0.610476
##  [739] -0.814491  0.192092 -1.355650 -0.406531  0.144119 -0.836939
##  [745]  0.164692  1.118466 -0.449636 -1.126119 -0.510941  1.089987
##  [751] -0.236120  1.466219 -0.310185 -0.479641 -0.851434 -1.184374
##  [757] -0.770589 -0.919018  0.748976 -0.568956 -0.029106  2.024044
##  [763] -0.456293 -0.120135 -1.997518  0.684919 -0.248661 -0.100254
##  [769]  2.350988 -0.586322 -0.537362 -0.005425 -0.733762 -1.513456
##  [775] -0.741013 -1.285568  0.449554 -1.641927  0.135350 -0.174605
##  [781] -0.693085  1.609487  0.093101 -0.755245 -1.035733 -0.271449
##  [787] -0.995305  2.210312  0.919975  0.184409 -1.121979 -0.742921
##  [793] -2.113518 -0.087474 -1.194039  1.963299 -0.344190 -1.595020
##  [799] -0.475464 -2.039189 -1.243071 -1.717083  0.848228  0.257838
##  [805] -0.225256 -1.622531 -0.331424  1.171473 -0.057519 -0.553254
##  [811] -0.856233 -1.697106  1.412921  1.233791 -0.417074 -0.784890
##  [817]  0.764882  1.548579  1.131459  0.843523  2.380642 -1.237022
##  [823] -0.534841 -0.669692  0.225022 -0.677562 -0.399769 -1.594106
##  [829] -0.735286 -0.323773 -0.385888 -1.557128 -0.090699 -0.758786
##  [835] -0.700739 -0.332504 -0.368568 -0.326241 -0.473265  2.490657
##  [841]  0.575098  0.096685 -1.350963 -0.711480  0.546858 -1.121298
##  [847] -0.114444  1.788857 -0.366737  1.504996  0.238439 -0.120096
##  [853] -2.117985  1.256079  0.654766 -2.428001 -0.264692  0.738743
##  [859] -0.540685 -0.236891 -0.485915 -0.452986 -0.117027 -1.824899
##  [865]  0.015927 -0.141818 -0.452951  0.331972 -0.829109  0.270037
##  [871]  1.243081 -0.276046  0.672054  0.170743 -1.061476  0.189492
##  [877]  0.118481 -0.220278 -0.324645 -0.994817  0.014379 -0.635001
##  [883] -0.578855  0.891387 -1.950256 -0.015028  0.128552  1.064012
##  [889] -0.227756 -1.205595  0.307463 -0.574068 -0.581930 -0.483400
##  [895]  1.551062  0.814020 -0.611864  0.117453  0.373122  0.282991
##  [901] -0.437605  0.096941 -0.031506 -1.164482 -0.673372  0.199444
##  [907] -0.107448  0.248440  0.854979 -1.361208  2.029402 -0.104235
##  [913]  1.720246 -0.831626 -0.994812 -0.514152  0.031354 -0.442830
##  [919] -0.936703  0.229252 -0.623478  0.601027 -1.439294  0.197543
##  [925] -1.151606  0.891598  0.909457  0.504282 -1.265414 -0.917977
##  [931] -0.143972 -0.291550 -0.974948  1.888579 -1.492694  0.760921
##  [937] -0.285592  0.143975 -0.435713  0.207472  1.635906 -1.147197
##  [943] -1.192355  0.994621 -0.510871 -0.672770 -0.876866  0.026908
##  [949] -1.250336 -1.083352  0.310934 -0.080951  0.723331 -0.117984
##  [955]  2.741189 -0.326372  1.061630 -0.118636  0.497279  0.269175
##  [961]  0.459274  2.161641 -1.233543  0.250976 -0.238556  0.517179
##  [967]  0.232363 -0.299632  1.274529 -0.144269 -1.017638  0.192158
##  [973]  0.602167  0.240732  1.056025  0.237916  1.897035  0.564675
##  [979]  0.668800  1.048655 -0.830019  1.322315  0.492720 -0.136835
##  [985]  0.338899 -0.272234  1.042757  0.630720  0.465132 -0.543786
##  [991] -0.291580  0.353636  0.404591  1.840546 -0.026190  1.238292
##  [997] -0.248234  0.010031 -0.987354 -0.808132 -1.067622  0.182090
## [1003] -0.162440 -1.524472  1.367588 -1.615643  0.336026 -0.763109
## [1009] -0.507856  0.321277 -1.471311 -0.930557  0.549151 -0.821787
## [1015] -0.564380  0.287246 -0.267830 -1.093953  0.666230  0.889062
## [1021] -0.040237  1.241006  0.393899 -0.286174  0.514850  2.128409
## [1027] -0.850157  0.061360  0.128237 -0.132036  1.781431  0.457813
## [1033]  0.070716  0.674180  1.053520  2.040670  0.986228  0.633562
## [1039]  0.079473  1.007905 -0.168208 -0.901336 -1.317877 -0.901011
## [1045] -0.581093 -0.243983  0.113651 -0.136029 -1.190172 -0.718818
## [1051] -1.028581  0.050500  0.611814  0.758468 -0.151870 -0.467123
## [1057]  0.381383  0.087475 -1.083932 -1.268972  1.897311 -0.644020
## [1063] -0.647888 -0.320459 -1.294104  0.004257  0.132567 -0.584050
## [1069] -0.216849  0.891157  1.152426  0.191378  0.650663 -1.539938
## [1075]  0.008052 -0.535711  1.058493  1.878808  0.270114  0.080988
## [1081] -0.272953  0.870912 -0.316169  1.668138 -0.832412  0.635262
## [1087]  0.364334  0.333720  0.076506  0.321329  1.783462 -0.796710
## [1093]  1.443471  0.844264  0.391144 -1.008122 -0.459523 -0.697750
## [1099]  0.801868  0.966445  0.666145  1.373202 -1.365309 -0.198631
## [1105]  2.353363  0.790351  1.190751 -0.236517  0.386475 -0.690428
## [1111] -0.840510 -0.918399  0.032135 -0.127501  0.101193  1.240038
## [1117] -0.386478 -0.884531 -1.234962 -0.221918 -0.183840  0.707760
## [1123] -0.473260 -0.418418 -0.266481  0.972148  0.245496  0.782405
## [1129] -0.183831  0.089969  1.945029 -0.676948 -1.001106 -0.467903
## [1135] -0.117725 -1.460559  1.111856 -0.007770  1.341705 -0.523277
## [1141]  0.803471 -1.075513 -0.213483 -0.442931  0.654036  0.411993
## [1147]  0.763418 -0.100218 -0.371953 -0.994398 -2.186784 -0.042015
## [1153]  1.520408 -1.427915  0.309908 -0.569566 -0.947245  0.007767
## [1159] -0.293956 -0.178610 -0.018940 -1.215898 -0.227310  0.850927
## [1165] -1.361863 -0.083139 -0.193327 -0.796988 -0.974983 -1.204759
## [1171]  0.879214  1.734794  1.721437 -0.510145  1.492570 -0.304864
## [1177]  0.064584 -1.334967 -0.280726  0.930980 -0.334117 -0.249488
## [1183] -1.860019  0.731797 -0.781630  0.023721  1.025039 -0.749503
## [1189]  0.379218  0.486904  0.867943  0.372261 -0.482300  1.223004
## [1195]  1.149287  1.748326  0.210497 -0.383964 -0.041371 -0.020947
## [1201]  0.083050  0.038160  0.310823  0.102791  0.544493 -0.711215
## [1207]  0.414937  0.362910 -0.331130  2.584657  0.413258  2.393041
## [1213]  0.000866  0.157240 -0.737155 -0.053489 -0.631421  1.577534
## [1219]  1.166093 -1.149709  1.074813 -0.830013 -0.954626 -0.773213
## [1225] -0.646941  0.094344 -0.981012 -1.394025 -0.673020  0.705396
## [1231] -0.258895 -0.910460  0.539646 -1.028530 -0.574719  0.399911
## [1237]  1.149728 -1.612501  0.014605 -1.968110 -0.917816 -0.748017
## [1243] -0.583989  3.120193  0.098284 -0.201297  1.823638  0.422475
## [1249] -0.849126 -0.612296  1.016312  1.071492 -0.677758  0.945465
## [1255]  1.113798 -0.413281  0.417644 -0.540702 -1.724950  0.063627
## [1261] -1.577849 -0.456725 -0.767740 -0.361407  0.391754  0.520809
## [1267]  0.332655 -0.818927 -1.491234 -0.715105 -0.477667  0.723670
## [1273] -0.432364  0.621093  2.000434  1.999094  0.208875  0.301941
## [1279] -0.800294 -0.546827 -0.188945  0.149134 -0.081709  0.586816
## [1285]  1.232965  1.035646 -0.533368 -1.644527 -0.450339  0.120667
## [1291]  0.798030  1.147266  0.598542  1.417049 -0.664355  1.175759
## [1297]  0.017247  1.553065 -1.315966  0.077685  0.114773 -0.599683
## [1303] -0.143861  1.979916 -0.056811  0.125926  0.058467 -0.580142
## [1309]  0.938374  0.859303 -0.004959 -1.010901  1.721801  0.181688
## [1315] -0.008925 -0.706477 -0.809098  0.466337  1.174049 -0.890749
## [1321] -0.290480  0.140512 -1.066701 -0.162724  0.913876  0.182093
## [1327] -1.707630 -0.151938 -1.115889 -0.345718 -1.799280 -0.728625
## [1333]  0.193404  0.493015  0.211195  0.154792 -1.167833 -0.288130
## [1339] -0.433538  0.041155  0.134155 -0.281660  0.296543 -0.522004
## [1345]  0.660912  0.295812 -1.412066 -0.706419 -1.349744 -1.602515
## [1351]  0.503729  1.620320  0.624710  0.362223  0.339516 -0.504305
## [1357]  0.248085  1.074137  0.544420 -0.964354  0.083053  0.464403
## [1363] -0.730766 -0.787663  1.027084  0.440622  0.661940  0.349933
## [1369]  1.297297 -0.380095  0.221551  0.340573 -0.731281 -0.381273
## [1375] -2.319438 -0.128993 -1.108902 -1.222017  0.107326  1.447903
## [1381] -0.037868  0.084358  0.126635 -0.533170  0.250115 -1.302421
## [1387] -0.501502 -0.213202  0.829448  0.564748 -0.334521  0.047215
## [1393] -1.227107  0.608760  0.248151  1.294125  0.621833 -0.632764
## [1399] -1.435893  1.378102  0.384647 -1.001929 -1.044417 -0.889246
## [1405]  0.068187  0.249969 -0.742544 -0.172475 -0.235387 -0.085324
## [1411] -0.036207 -1.452086  0.060229  0.520544  0.971745  0.070890
## [1417] -0.423808 -0.160730  1.163104 -1.672498 -0.549346 -0.351720
## [1423] -2.216412  0.764759 -0.055147  0.160405 -2.335960  0.659332
## [1429] -0.824221 -0.313561  0.953195 -0.573586 -0.943404  0.749211
## [1435]  0.245496  0.895515  0.265141  0.327943  0.765701  0.960396
## [1441]  0.948656 -1.811873  2.371657 -1.396416  0.809240  0.615814
## [1447]  0.006032 -0.533996  0.620446  1.833686 -1.180984 -0.216997
## [1453]  0.105278  0.164653 -0.749561  0.762221  0.203365  2.741061
## [1459] -0.554371 -0.390834  0.136948 -0.929317  1.334971  1.455815
## [1465] -0.444241  0.429476  0.583481 -1.457492  0.481673 -1.095855
## [1471]  0.895581  0.622004  0.103838 -0.292397 -0.976981 -0.012257
## [1477] -0.679324  1.257062  2.081028  0.277605  1.777812  0.276458
## [1483] -0.635691  0.521238  0.190248  0.338084 -0.145818  0.679051
## [1489]  0.934888  1.477755  0.517500 -1.278657 -1.395789  0.556023
## [1495]  0.483035  0.549854 -0.074575  0.237516 -0.852524  0.685479
## [1501]  1.226458  0.411165  0.416461  0.528073 -0.643064  1.042848
## [1507]  0.174053  0.156036  1.373336 -0.549160 -0.186527 -0.609631
## [1513] -0.944209  0.665537  1.091871 -0.848554 -0.240357  0.636399
## [1519] -0.700420 -0.865397 -0.292525 -1.365828 -1.012102 -1.023136
## [1525] -0.754552  1.162505 -1.292965  1.492053  0.251690 -1.713331
## [1531] -0.847002 -0.359851  0.024643 -0.931598  0.991218  0.084337
## [1537] -0.863497 -1.126621  0.707559  1.197507 -0.102608  2.235031
## [1543] -0.224683 -0.141208  0.487582 -0.220590  0.321052  0.102193
## [1549] -1.811959  0.177998  0.462423  0.523333 -0.937653  1.097605
## [1555] -1.195530 -1.084594  2.105960  0.921949  0.839169 -2.194238
## [1561]  1.708977 -1.219005  2.099283  1.307718 -0.190547 -0.275561
## [1567] -0.629747  0.349563 -1.033720 -0.251976 -0.012042 -0.465169
## [1573] -0.199434 -0.518455 -1.188894 -0.212053  0.367896 -0.994645
## [1579]  1.086423  0.152645  0.173143  1.530108  0.367999 -0.117112
## [1585] -0.949737  0.074173 -0.878305  0.530112  0.304187 -0.478350
## [1591] -0.888882 -0.684955  0.115719  0.018966 -0.350871 -0.566578
## [1597]  0.450698  0.267876 -0.060388  1.087920  0.297311  0.026231
## [1603] -0.131478  0.525840 -1.235846 -0.463059  0.152476  1.277618
## [1609] -0.236178  0.028341 -0.858597 -0.365755 -1.983185 -0.399271
## [1615] -1.133974 -1.341495  0.328454 -2.021155  0.207182 -0.402390
## [1621] -0.895652 -1.233166  1.380190  1.027202 -1.054337  0.016220
## [1627] -1.704101  0.100041 -1.359891 -0.662863 -0.782190 -0.565520
## [1633] -0.447361 -2.033689 -0.762229  1.961136  0.823408  0.857056
## [1639]  0.622728 -1.134369  0.503988 -0.602631  0.396333 -0.382084
## [1645]  0.293975  1.345165 -0.666377  1.955652  0.342998 -0.129540
## [1651]  0.312613 -0.877455 -0.358761 -1.039092  1.374540  1.138435
## [1657]  1.758016  0.215308 -0.087209  0.319846  0.071485  1.106349
## [1663]  0.057123 -0.657171  0.039278  0.804821  1.758121  1.259729
## [1669] -0.427134  2.434847 -0.982182  1.251987  0.465355  0.945226
## [1675] -1.095621 -0.039843 -0.259751 -0.507319 -0.747538  0.918467
## [1681] -0.196893  0.897721 -0.671597  1.525072  0.216865 -0.286760
## [1687]  0.803811  0.420569  1.542062 -0.089843  1.132806 -0.588290
## [1693] -0.777363  1.764165  0.668949  0.295593 -1.235044 -0.476077
## [1699]  0.874269 -0.124674  0.319045  1.133356 -0.637228  1.229820
## [1705] -1.886446  1.612052  0.039708 -0.173666  1.173693  0.044611
## [1711]  2.470091  0.189748  0.959394 -0.874784  0.110421  0.514886
## [1717]  0.457936 -0.814763  2.197350 -0.699283 -0.977402 -0.381255
## [1723]  0.159085  0.165367 -0.391066  0.055121  0.940936 -0.305034
## [1729] -0.724882 -0.452347 -0.348445 -0.330763 -0.847443  0.138566
## [1735] -0.250533  0.214287  0.592215  0.249667 -0.614059 -0.021386
## [1741] -0.525043  0.222215  1.675852  0.439602  0.212722 -0.376202
## [1747] -0.307964  0.130467 -0.236114 -0.424582 -0.299094  0.633589
## [1753] -0.162677 -0.835662  1.663003  0.765843 -1.026879  0.009112
##   [1] "Vote 1"   "Vote 2"   "Vote 3"   "Vote 4"   "Vote 5"   "Vote 6"  
##   [7] "Vote 7"   "Vote 8"   "Vote 9"   "Vote 10"  "Vote 11"  "Vote 12" 
##  [13] "Vote 13"  "Vote 14"  "Vote 15"  "Vote 16"  "Vote 17"  "Vote 18" 
##  [19] "Vote 19"  "Vote 20"  "Vote 21"  "Vote 23"  "Vote 24"  "Vote 26" 
##  [25] "Vote 27"  "Vote 28"  "Vote 29"  "Vote 30"  "Vote 31"  "Vote 32" 
##  [31] "Vote 33"  "Vote 34"  "Vote 35"  "Vote 36"  "Vote 37"  "Vote 38" 
##  [37] "Vote 39"  "Vote 40"  "Vote 41"  "Vote 42"  "Vote 44"  "Vote 45" 
##  [43] "Vote 46"  "Vote 47"  "Vote 48"  "Vote 49"  "Vote 50"  "Vote 51" 
##  [49] "Vote 52"  "Vote 53"  "Vote 54"  "Vote 55"  "Vote 56"  "Vote 57" 
##  [55] "Vote 58"  "Vote 59"  "Vote 60"  "Vote 61"  "Vote 62"  "Vote 63" 
##  [61] "Vote 64"  "Vote 65"  "Vote 66"  "Vote 68"  "Vote 69"  "Vote 70" 
##  [67] "Vote 71"  "Vote 72"  "Vote 73"  "Vote 74"  "Vote 75"  "Vote 77" 
##  [73] "Vote 78"  "Vote 79"  "Vote 80"  "Vote 82"  "Vote 83"  "Vote 84" 
##  [79] "Vote 85"  "Vote 86"  "Vote 87"  "Vote 88"  "Vote 89"  "Vote 90" 
##  [85] "Vote 91"  "Vote 92"  "Vote 93"  "Vote 94"  "Vote 95"  "Vote 96" 
##  [91] "Vote 97"  "Vote 98"  "Vote 99"  "Vote 100" "Vote 101" "Vote 102"
##  [97] "Vote 103" "Vote 104" "Vote 105" "Vote 106" "Vote 107" "Vote 108"
## [103] "Vote 109" "Vote 110" "Vote 111" "Vote 112" "Vote 113" "Vote 114"
## [109] "Vote 115" "Vote 116" "Vote 117" "Vote 118" "Vote 119" "Vote 120"
## [115] "Vote 122" "Vote 123" "Vote 124" "Vote 125" "Vote 126" "Vote 127"
## [121] "Vote 129" "Vote 131" "Vote 132" "Vote 133" "Vote 134" "Vote 135"
## [127] "Vote 136" "Vote 137" "Vote 138" "Vote 139" "Vote 140" "Vote 141"
## [133] "Vote 142" "Vote 143" "Vote 144" "Vote 145" "Vote 146" "Vote 147"
## [139] "Vote 148" "Vote 149" "Vote 150" "Vote 151" "Vote 152" "Vote 153"
## [145] "Vote 154" "Vote 155" "Vote 156" "Vote 157" "Vote 158" "Vote 159"
## [151] "Vote 160" "Vote 161" "Vote 162" "Vote 163" "Vote 164" "Vote 165"
## [157] "Vote 166" "Vote 167" "Vote 168" "Vote 169" "Vote 170" "Vote 171"
## [163] "Vote 172" "Vote 173" "Vote 174" "Vote 175" "Vote 176" "Vote 177"
## [169] "Vote 178" "Vote 179" "Vote 180" "Vote 181" "Vote 182" "Vote 183"
## [175] "Vote 184" "Vote 185" "Vote 186" "Vote 187" "Vote 188" "Vote 189"
## [181] "Vote 190" "Vote 191" "Vote 192" "Vote 193" "Vote 194"

Next, compare the fit of the models, presented in table 2 of the paper.

phat <- predict(out1, cutoff=.88)
## predict.ideal: Working with rollcall object vot 
## 
## Using posterior means in ideal object.
phat2 <- predict(out2, cutoff=.88)
## predict.ideal: Working with rollcall object vot 
## 
## Using posterior means in ideal object.
phat.table <- round(rbind(
  phat$party.percent,
  phat2$party.percent,
  phat2$party.percent - phat$party.percent),3)
phat.table
##      council ALDE/ADLE   ECR    EFD    EPP Greens/EFA GUE-NGL     NI
## [1,]  85.806    95.015 70.38 80.939 97.850     90.002  84.169 81.930
## [2,]  91.484    97.096 89.11 85.808 98.617     95.953  88.015 89.015
## [3,]   5.678     2.081 18.73  4.869  0.767      5.951   3.846  7.085
##         S&D
## [1,] 96.710
## [2,] 97.648
## [3,]  0.938

The next chunk of code makes the plots presented in figure 3 of the paper.

library(car)
cols <- c(recode(vot$legis.data$party,"'ALDE/ADLE'=1;'ECR'=7;
                 'EFD'=8;'EPP'=4;'Greens/EFA'=3;'GUE-NGL'=5;'S&D'=2;else=9"))
votingweights <- c(12,10,12,7,29,4,7,12,27,29,7,
                   29,4,4,7,4,12,3,13,10,27,12,14,4,7,7,10,29)
## calculate group mean and sd in 2d, 
gr.mean <- aggregate(out2$xbar,by=list(vot$legis.data$partyName),FUN=mean)
gr.sd <- aggregate(out2$xbar,by=list(vot$legis.data$partyName),FUN=var)
gr.mean <- gr.mean[-1,]
gr.sd <- gr.sd[-1,]

plot(x=gr.mean$D1,y=gr.mean$D2,type="n",xlim=c(-1.75,2),ylim=c(-2,2.5),
     bty="n",main="Budget votes: Political groups",ylab="2nd dimension",xlab="1st dimension")
points(out2$xbar,pch=16,cex=.5,col="grey")
text(x=gr.mean$D1,y=gr.mean$D2+.2,labels=gr.mean$Group.1,cex=1.5)

plot of chunk unnamed-chunk-6

plot(out2$xbar[1:28,],xlim=c(-1.75,2),ylim=c(-2,2.5),type="n",
     bty="n",main="Budget votes: Council members",ylab="2nd dimension",xlab="1st dimension")
text(out2$xbar[1:28,],labels=rownames(out2$xbar)[1:28],cex=.9)

plot of chunk unnamed-chunk-6

gr1 <- rownames(out2$xbar)[1:28][out2$xbar[1:28,1]< -.5 & out2$xbar[1:28,2]<0]
#legend("bottomleft",legend=gr1,cex=.6)
gr2 <- rownames(out2$xbar)[1:28][out2$xbar[1:28,1]> -.3 &  out2$xbar[1:28,1]< .3 & out2$xbar[1:28,2]< 0]
#legend(0,-1.35,legend=gr2,cex=.6)
gr3 <- rownames(out2$xbar)[1:28][out2$xbar[1:28,1]> .3 &  out2$xbar[1:28,1]< .7 & out2$xbar[1:28,2]< -.4]
#legend(.5,-1.2,legend=gr3,cex=.6)

plot(x=gr.mean$D1,y=gr.mean$D2,type="n",xlim=c(-1.75,2),ylim=c(-2,2.5),
     bty="n",main="Budget votes: Council and EP",ylab="2nd dimension",xlab="1st dimension")
points(out2$xbar,pch=16,cex=.5,col="grey")
text(x=gr.mean$D1,y=gr.mean$D2+.2,labels=gr.mean$Group.1,cex=1.5)
text(out2$xbar[1:28,],labels=rownames(out2$xbar)[1:28],cex=1.1)

plot of chunk unnamed-chunk-6

The final chunk of code shows how different votes separated on the first and second dimension. Note that there is no pure second dimension votes.

discr1 <- t(apply(out2$beta[,,1],2,quantile,c(.1,.9)))
overlaps1 <-discr1[,1]<0 & discr1[,2]>0 
sum(overlaps1==FALSE)
## [1] 185
sum(overlaps1==TRUE)
## [1] 0
discr2 <- t(apply(out2$beta[,,2],2,quantile,c(.1,.9)))
overlaps2 <- discr2[,1]<0 & discr2[,2]>0
sum(overlaps2==FALSE)
## [1] 170
sum(overlaps2==TRUE)
## [1] 15
sum(overlaps1==TRUE & overlaps2==FALSE)
## [1] 0
sum(overlaps1==FALSE & overlaps2==FALSE)
## [1] 170
vot$vote.data[overlaps1==FALSE & overlaps2==TRUE,]# Pure 1 dimension votes
##             EP.date
## Vote 9   2010-03-09
## Vote 12  2010-03-25
## Vote 15  2010-06-15
## Vote 17  2010-06-15
## Vote 18  2010-06-15
## Vote 19  2010-06-15
## Vote 41  2010-11-11
## Vote 61  2010-12-14
## Vote 108 2011-12-01
## Vote 115 2011-12-15
## Vote 146 2012-10-23
## Vote 148 2012-11-21
## Vote 173 2013-09-11
## Vote 182 2013-11-19
## Vote 187 2013-11-20
##                                                                                                                                                                                                                 EP.ref
## Vote 9                                                                                                                                           Mobilisation of the European Globilisation Adjustment Fund: Lithuania
## Vote 12                                                                                                           Mobilisation of the European Globalisation Adjustment Fund: Lithuania/Manufacture of wearing apparel
## Vote 15                                                                                                                                                  European Globalisation Adjustment Fund: ES/Region of Valencia
## Vote 17                                                                                                                                           Mobilisation of European Globalisation Adjustment Fund : ES/Castilla
## Vote 18                                                                                                                             Mobilisation of European Globalisation Adjustment Fund : Ireland/Waterford Crystal
## Vote 19                                                                                           Mobilisation of the European Globalisation Adjustment Fund: technical assistance at the initiative of the Commission
## Vote 41                                                                                                                                            Mobilisation of the European Globalisation Adjustment Fund: Ireland
## Vote 61                                                                                                               Mobilisation of the European Globalisation Adjustment Fund: Wielkopolskie Automotive from Poland
## Vote 108                                                                                                           Draft amending budget No 6/2011: Own resources, Integrated Maritime Policy, Greece, ESF, Palestine 
## Vote 115                                                                                                  Mobilisation of the European Globalisation Adjustment Fund (application EGF/2009/019 FR/Renault from France)
## Vote 146                                                                                                                                                                     Own resource based on the value added tax
## Vote 148 Draft Amending Budget No 5/2012: Solidarity Fund response to earthquakes in Emilia-Romagna (Italy) and modification of the budget line for the preparatory action for the European Year of Volunteering 2011 
## Vote 173          Draft amending budget No 4/2013 – Staff of the European GNSS Agency – Staff of the Education, Audiovisual and Culture Executive Agency (EACEA) – Staff of the Court of Justice of the European Union
## Vote 182                                                                                                                                                                               Draft amending budget No 7/2013
## Vote 187        Draft amending budget No 9/2013: Mobilisation of the EU Solidarity Fund for Romania (Drought and forest fires in 2012) and for Germany, Austria and the Czech Republic (Flooding in May and June 2013)
vot$vote.data[overlaps1==TRUE & overlaps2==FALSE,] # Pure 2 dimension, NONE 
## [1] EP.date EP.ref 
## <0 rows> (or 0-length row.names)