Three variables in the analysis:

Import data

# 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 variables to plain English

# 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"

Explore

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: