Three variables in the analysis:
# Import data
data <- read.csv("data_fjc/data_merged.csv")
# Sturecture of data
str(data)
## 'data.frame': 4200 obs. of 51 variables:
## $ CIRCUIT : int 1 1 1 1 1 1 1 1 1 1 ...
## $ DISTRICT : int 2 2 2 2 2 2 2 2 2 2 ...
## $ OFFICE : int 1 1 1 1 1 1 1 1 1 1 ...
## $ DOCKET : int 265 409 100015 100016 100018 100019 100020 100028 100030 100031 ...
## $ ORIGIN : int 4 4 1 1 5 1 1 5 1 1 ...
## $ FILEDATE : Factor w/ 2566 levels "2001-01-02","2001-01-04",..: 33 40 4 4 5 5 5 8 8 8 ...
## $ FILEYEAR : int 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 ...
## $ FDATEUSE : Factor w/ 204 levels "1/1/2001","1/1/2002",..: 86 103 1 1 1 1 1 1 1 1 ...
## $ JURIS : int 3 4 1 1 4 3 4 4 4 4 ...
## $ NOS : int 840 190 190 190 190 440 110 365 365 365 ...
## $ TITLE : Factor w/ 33 levels "-8","0","10",..: 5 13 13 13 13 20 13 20 13 13 ...
## $ SECTION : Factor w/ 144 levels "-8","1","10",..: 10 20 27 27 20 73 22 138 20 20 ...
## $ SUBSECT : Factor w/ 73 levels "-8","1","12",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ RESIDENC : int -8 43 -8 -8 25 -8 52 55 15 15 ...
## $ CLASSACT : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ DEMANDED : int 0 0 0 0 0 0 0 0 0 0 ...
## $ FILEJUDG : logi NA NA NA NA NA NA ...
## $ FILEMAG : logi NA NA NA NA NA NA ...
## $ COUNTY : int 99999 33015 33013 33013 88888 88888 88888 88888 33007 33015 ...
## $ ARBIT : Factor w/ 4 levels "-8","E","M","V": 1 1 1 1 1 1 1 1 1 1 ...
## $ MDLDOCK : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ PLT : Factor w/ 3128 levels "-8","108 DEGREES. LLC",..: 2968 1362 2944 2944 1546 268 85 1813 2166 1767 ...
## $ DEF : Factor w/ 3369 levels "-8",", ET AL",..: 1024 1637 993 2405 3274 649 2845 77 118 119 ...
## $ TRANSDAT : logi NA NA NA NA NA NA ...
## $ TRANSOFF : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ TRANSDOC : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ TRANSORG : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ TERMDATE : Factor w/ 2560 levels "2001-01-25","2001-02-05",..: 6 33 19 7 4 32 29 3 5 2 ...
## $ TDATEUSE : Factor w/ 204 levels "1/1/2001","1/1/2002",..: 86 171 120 86 86 171 154 69 86 69 ...
## $ TRCLACT : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ TERMJUDG : logi NA NA NA NA NA NA ...
## $ TERMMAG : logi NA NA NA NA NA NA ...
## $ PROCPROG : int 5 4 2 2 2 2 5 2 1 2 ...
## $ DISP : int 5 13 18 18 14 3 6 14 10 12 ...
## $ NOJ : int 2 -8 0 0 -8 -8 2 -8 -8 -8 ...
## $ AMTREC : int 5 54 0 0 0 0 33 0 0 0 ...
## $ JUDGMENT : int 1 -8 -8 -8 -8 -8 2 -8 -8 -8 ...
## $ DJOINED : Factor w/ 1512 levels "","1/10/2005",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ PRETRIAL : Factor w/ 418 levels "","1/10/2012",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ TRIBEGAN : Factor w/ 40 levels "","1/20/2016",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ TRIALEND : Factor w/ 83 levels "","1/13/2004",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ TRMARB : int -8 -8 -8 -8 -8 -8 -8 -8 -8 -8 ...
## $ PROSE : int 0 0 0 0 0 1 2 0 0 0 ...
## $ IFP : Factor w/ 2 levels "-8","FP": 1 1 1 1 1 1 1 1 1 1 ...
## $ STATUSCD : Factor w/ 1 level "L": 1 1 1 1 1 1 1 1 1 1 ...
## $ TAPEYEAR : int 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 ...
## $ nature_of_suit: Factor w/ 44 levels "ADMINISTRATIVE PROCEDURE ACT/REVIEW OR APPEAL OF AGENCY DECISION",..: 43 29 29 29 29 28 19 36 36 36 ...
## $ busType_def : Factor w/ 5 levels "CORP","LLC","PARTNERSHIP",..: NA NA NA NA NA NA NA NA NA NA ...
## $ busType_plt : Factor w/ 4 levels "CORP","LLC","PARTNERSHIP",..: NA NA NA NA NA NA NA NA NA NA ...
## $ busType : Factor w/ 3 levels "Both","Neither",..: 2 2 2 2 2 2 2 2 2 2 ...
## $ cause : Factor w/ 173 levels "","05:551 Administrative Procedure Act",..: NA NA NA NA NA NA NA NA NA NA ...
# See the first six rows of the data
head(data)
## CIRCUIT DISTRICT OFFICE DOCKET ORIGIN FILEDATE FILEYEAR FDATEUSE JURIS
## 1 1 2 1 265 4 2001-03-21 2001 3/1/2001 3
## 2 1 2 1 409 4 2001-04-01 2001 4/1/2001 4
## 3 1 2 1 100015 1 2001-01-10 2001 1/1/2001 1
## 4 1 2 1 100016 1 2001-01-10 2001 1/1/2001 1
## 5 1 2 1 100018 5 2001-01-12 2001 1/1/2001 4
## 6 1 2 1 100019 1 2001-01-12 2001 1/1/2001 3
## NOS TITLE SECTION SUBSECT RESIDENC CLASSACT DEMANDED FILEJUDG FILEMAG
## 1 840 15 1114 -8 -8 -8 0 NA NA
## 2 190 28 1332 -8 43 -8 0 NA NA
## 3 190 28 1345 -8 -8 -8 0 NA NA
## 4 190 28 1345 -8 -8 -8 0 NA NA
## 5 190 28 1332 -8 25 -8 0 NA NA
## 6 440 42 1983 -8 -8 -8 0 NA NA
## COUNTY ARBIT MDLDOCK PLT
## 1 99999 -8 -8 VELCRO INDUSTRIES BV, ET AL
## 2 33015 -8 -8 HIGHDATA SOFTWARE
## 3 33013 -8 -8 USA
## 4 33013 -8 -8 USA
## 5 88888 -8 -8 KAPUR
## 6 88888 -8 -8 BICKFORD
## DEF TRANSDAT TRANSOFF TRANSDOC TRANSORG
## 1 FASTECH, ET AL NA -8 -8 -8
## 2 KOTHANDAN NA -8 -8 -8
## 3 EVANS NA -8 -8 -8
## 4 PICUCCI NA -8 -8 -8
## 5 WEBMANAGE TECHNOLOG, ET AL NA -8 -8 -8
## 6 CONCORD DISTRICT CT NA -8 -8 -8
## TERMDATE TDATEUSE TRCLACT TERMJUDG TERMMAG PROCPROG DISP NOJ AMTREC
## 1 2001-03-22 3/1/2001 -8 NA NA 5 5 2 5
## 2 2001-08-15 8/1/2001 -8 NA NA 4 13 -8 54
## 3 2001-05-17 5/1/2001 -8 NA NA 2 18 0 0
## 4 2001-03-23 3/1/2001 -8 NA NA 2 18 0 0
## 5 2001-03-01 3/1/2001 -8 NA NA 2 14 -8 0
## 6 2001-08-10 8/1/2001 -8 NA NA 2 3 -8 0
## JUDGMENT DJOINED PRETRIAL TRIBEGAN TRIALEND TRMARB PROSE IFP STATUSCD
## 1 1 -8 0 -8 L
## 2 -8 -8 0 -8 L
## 3 -8 -8 0 -8 L
## 4 -8 -8 0 -8 L
## 5 -8 -8 0 -8 L
## 6 -8 -8 1 -8 L
## TAPEYEAR nature_of_suit busType_def busType_plt busType cause
## 1 2001 TRADEMARK <NA> <NA> Neither <NA>
## 2 2001 OTHER CONTRACT ACTIONS <NA> <NA> Neither <NA>
## 3 2001 OTHER CONTRACT ACTIONS <NA> <NA> Neither <NA>
## 4 2001 OTHER CONTRACT ACTIONS <NA> <NA> Neither <NA>
## 5 2001 OTHER CONTRACT ACTIONS <NA> <NA> Neither <NA>
## 6 2001 OTHER CIVIL RIGHTS <NA> <NA> Neither <NA>
# Basic descriptive statistics of data
summary(data)
## CIRCUIT DISTRICT OFFICE DOCKET ORIGIN
## Min. :1 Min. :2 Min. :1 Min. : 73 Min. : 1.000
## 1st Qu.:1 1st Qu.:2 1st Qu.:1 1st Qu.: 400138 1st Qu.: 1.000
## Median :1 Median :2 Median :1 Median : 800364 Median : 1.000
## Mean :1 Mean :2 Mean :1 Mean : 855885 Mean : 1.467
## 3rd Qu.:1 3rd Qu.:2 3rd Qu.:1 3rd Qu.:1200343 3rd Qu.: 2.000
## Max. :1 Max. :2 Max. :1 Max. :9900606 Max. :13.000
##
## FILEDATE FILEYEAR FDATEUSE JURIS
## 2002-09-16: 10 Min. :2001 10/1/2002: 50 Min. :1.000
## 2003-11-25: 9 1st Qu.:2004 5/1/2002 : 40 1st Qu.:3.000
## 2002-09-24: 8 Median :2008 9/1/2002 : 40 Median :3.000
## 2004-05-07: 7 Mean :2008 10/1/2003: 36 Mean :3.315
## 2010-11-23: 7 3rd Qu.:2012 4/1/2013 : 36 3rd Qu.:4.000
## 2002-09-09: 6 Max. :2017 6/1/2005 : 34 Max. :4.000
## (Other) :4153 (Other) :3964
## NOS TITLE SECTION SUBSECT
## Min. :110.0 28 :2717 1332 :1147 -8 :1562
## 1st Qu.:350.0 42 : 656 1441 : 912 CV : 430
## Median :440.0 15 : 396 1983 : 355 PI : 269
## Mean :443.9 29 : 112 1331 : 322 BC : 249
## 3rd Qu.:446.0 17 : 63 1692 : 163 ED : 229
## Max. :899.0 47 : 55 2000 : 146 OC : 177
## (Other): 201 (Other):1155 (Other):1284
## RESIDENC CLASSACT DEMANDED FILEJUDG
## Min. :-8.000 Min. :-8.000 Min. : 0.00 Mode:logical
## 1st Qu.:-8.000 1st Qu.:-8.000 1st Qu.: 0.00 NA's:4200
## Median :-8.000 Median :-8.000 Median : 0.00
## Mean : 6.339 Mean :-7.916 Mean : 2.64
## 3rd Qu.:15.000 3rd Qu.:-8.000 3rd Qu.: 0.00
## Max. :64.000 Max. : 1.000 Max. :5000.00
##
## FILEMAG COUNTY ARBIT MDLDOCK
## Mode:logical Min. :33001 -8:4180 Min. : -8.000
## NA's:4200 1st Qu.:33011 E : 7 1st Qu.: -8.000
## Median :33013 M : 5 Median : -8.000
## Mean :46637 V : 8 Mean : 9.216
## 3rd Qu.:33019 3rd Qu.: -8.000
## Max. :99999 Max. :2320.000
##
## PLT DEF TRANSDAT
## USA : 82 -8 : 61 Mode:logical
## -8 : 20 TYCO INTERNATIONAL, ET AL : 34 NA's:4200
## DIRECTV, INC.: 20 USA : 34
## AMATUCCI : 17 GUTIERREZ, ET AL : 12
## WILSON : 15 NH DEPARTMENT OF HEALTH AND HU: 12
## JOHNSON : 13 SEALED : 11
## (Other) :4033 (Other) :4036
## TRANSOFF TRANSDOC TRANSORG TERMDATE TDATEUSE
## Min. :-8 Min. :-8 Min. :-8 2006-03-03: 13 3/1/2006 : 43
## 1st Qu.:-8 1st Qu.:-8 1st Qu.:-8 2015-02-04: 13 12/1/2011: 42
## Median :-8 Median :-8 Median :-8 2004-10-14: 9 4/1/2003 : 35
## Mean :-8 Mean :-8 Mean :-8 2006-03-06: 9 10/1/2003: 34
## 3rd Qu.:-8 3rd Qu.:-8 3rd Qu.:-8 2011-12-19: 8 10/1/2006: 33
## Max. :-8 Max. :-8 Max. :-8 2004-07-01: 7 3/1/2005 : 33
## (Other) :4141 (Other) :3980
## TRCLACT TERMJUDG TERMMAG PROCPROG
## Min. :-8.000 Mode:logical Mode:logical Min. : 1.000
## 1st Qu.:-8.000 NA's:4200 NA's:4200 1st Qu.: 2.000
## Median :-8.000 Median : 5.000
## Mean :-7.854 Mean : 4.229
## 3rd Qu.:-8.000 3rd Qu.: 5.000
## Max. : 3.000 Max. :13.000
##
## DISP NOJ AMTREC JUDGMENT
## Min. : 0.0 Min. :-8.000 Min. : 0.00 Min. :-8.00
## 1st Qu.: 6.0 1st Qu.:-8.000 1st Qu.: 0.00 1st Qu.:-8.00
## Median :13.0 Median : 0.000 Median : 0.00 Median : 0.00
## Mean :10.5 Mean :-3.177 Mean : 35.09 Mean :-3.25
## 3rd Qu.:13.0 3rd Qu.: 0.000 3rd Qu.: 0.00 3rd Qu.: 0.00
## Max. :20.0 Max. : 6.000 Max. :9999.00 Max. : 4.00
##
## DJOINED PRETRIAL TRIBEGAN TRIALEND
## :2163 :3717 :4160 :4118
## 7/1/2013 : 8 10/12/2011: 7 2/17/2016: 2 1/13/2004: 1
## 11/14/2011: 6 10/24/2011: 4 1/20/2016: 1 1/20/2016: 1
## 10/12/2006: 5 3/5/2012 : 4 1/4/2011 : 1 1/23/2007: 1
## 10/22/2004: 5 11/24/2009: 3 1/6/2015 : 1 1/27/2009: 1
## 5/14/2007 : 5 12/16/2011: 3 1/6/2016 : 1 1/27/2016: 1
## (Other) :2008 (Other) : 462 (Other) : 34 (Other) : 77
## TRMARB PROSE IFP STATUSCD TAPEYEAR
## Min. :-8 Min. :0.000 -8:3943 L:4200 Min. :2001
## 1st Qu.:-8 1st Qu.:0.000 FP: 257 1st Qu.:2005
## Median :-8 Median :0.000 Median :2009
## Mean :-8 Mean :0.221 Mean :2009
## 3rd Qu.:-8 3rd Qu.:0.000 3rd Qu.:2013
## Max. :-8 Max. :3.000 Max. :2018
##
## nature_of_suit busType_def busType_plt
## OTHER CONTRACT ACTIONS : 610 CORP : 877 CORP : 409
## OTHER CIVIL RIGHTS : 574 LLC : 390 LLC : 264
## CIVIL RIGHTS JOBS : 437 PARTNERSHIP: 30 PARTNERSHIP: 4
## OTHER PERSONAL INJURY : 356 PC : 6 PC : 9
## OTHER STATUTORY ACTIONS: 344 PLLC : 2 NA's :3514
## INSURANCE : 245 NA's :2895
## (Other) :1634
## busType cause
## Both : 275 42:1983 Civil Rights Act : 183
## Neither :2484 28:1332 Diversity-Personal Injury : 79
## Only one:1441 28:1332 Diversity-Breach of Contract : 78
## 28:1441 Petition for Removal - Employment Discrim: 70
## 28:1331 Federal Question: Other Civil Rights : 68
## (Other) :1250
## NA's :2472
# Recode JUDGMENT to plain English
data$JUDGMENT[data$JUDGMENT == 1] <- "plaintiff"
data$JUDGMENT[data$JUDGMENT == 2] <- "defendant"
data$JUDGMENT[data$JUDGMENT == 3] <- "both"
data$JUDGMENT[data$JUDGMENT == 4] <- "unknown"
data$JUDGMENT[data$JUDGMENT %in% c(0,-8)] <- "missing"
# Recode Nauture of Judgment
data$NOJ[data$NOJ == 0] <- "no monetary award"
data$NOJ[data$NOJ == 1] <- "monetary award only"
data$NOJ[data$NOJ == 2] <- "monetary award and other"
data$NOJ[data$NOJ == 3] <- "injunction"
data$NOJ[data$NOJ == 4] <- "forfeiture/foreclosure/condemnation"
data$NOJ[data$NOJ == 5] <- "costs only"
data$NOJ[data$NOJ == 6] <- "costs and attorney fees"
data$NOJ[data$NOJ == -8] <- "missing"
library(dplyr)
data %>%
count(NOJ)
## # A tibble: 7 x 2
## NOJ n
## <chr> <int>
## 1 costs and attorney fees 5
## 2 costs only 2
## 3 injunction 17
## 4 missing 1702
## 5 monetary award and other 44
## 6 monetary award only 95
## 7 no monetary award 2335
data %>%
count(DEMANDED)
## # A tibble: 8 x 2
## DEMANDED n
## <int> <int>
## 1 0 4191
## 2 25 2
## 3 150 1
## 4 179 1
## 5 250 2
## 6 260 1
## 7 4950 1
## 8 5000 1
data %>%
filter(DEMANDED > 0) %>%
count(nature_of_suit, NOJ, DEMANDED)
## # A tibble: 8 x 4
## nature_of_suit NOJ DEMANDED n
## <fct> <chr> <int> <int>
## 1 CONSUMER CREDIT no monetary award 25 2
## 2 INSURANCE missing 250 1
## 3 MOTOR VEHICLE PERSONAL INJURY missing 250 1
## 4 NEGOTIABLE INSTRUMENTS no monetary award 4950 1
## 5 OTHER CONTRACT ACTIONS missing 260 1
## 6 OTHER CONTRACT ACTIONS no monetary award 150 1
## 7 OTHER CONTRACT ACTIONS no monetary award 179 1
## 8 OTHER PERSONAL INJURY no monetary award 5000 1
Key findings include: