***************************************************************************
* DATA LAYOUT FOR WEST VIRGINIA NIBRS DATA.
***************************************************************************.

***************************************************************************
* Reads in the Group A incident report data from a text delimited flat file.
* FILE TYPE MIXED defines each record as a case.  As a result the unit
* of analysis is determined by the level (record type) you wish to select.
* The SPSS data file resembles the structure of the original data file.
****************************************************************************.
file type mixed file = 'n:\new flat files as of 7-07\GroupA2005.txt'
  record = level 5 .
Record type 1.
data list /
 rdw 1-4 
 action 6-6 (A) 
 month 7-8
 year 9-12
 city 13-16
 ori 17-25 (A)
 incnumb 26-37(A)
 ainyear 38-41
 ainmon 42-43
 ainday 44-45
 ardi 46-46 (A)
 ainhour 47-48
 aclear 49-49 (A)
 acldatyr 50-53
 acldatmo 54-55
 acldatda 56-57
 aoff1 58-60 (a)
 aoff2 61-63 (a)
 aoff3 64-66 (a)
 aoff4 67-69 (a)
 aoff5 70-72 (a)
 aoff6 73-75 (a)
 aoff7 76-78 (a)
 aoff8 79-81 (a)
 aoff9 82-84 (a)
 aoff10 85-87 (a)
 aagid 88-92 (a)
 aagid2 93-96 (A)
 alight 97-97
 aweather 98-98
 antry1 99-100
 antry2 101-102
 axit1 103-104
 axit2 105-106
 asecur1 107-108
 asecur2 109-110
 atool1 111-112 (A)
 atool2 113-114 (A)
 avidnce 115-115 (A)
 avehicle 116-116 (a)
 avehmake 117-122 (A)
 avehmodl 123-126 (A)
 avehyear 127-128
 akeys 129-129 (A)
 avehlock 130-130 (A).
Record type 2.
data list /
  rdw 1-4 
  action 6-6 (A) 
  month 7-8
  year 9-12
  city 13-16
  ori 17-25 (A)
  incnumb 26-37(A)
  bucrcode 38-40(A)
  battempt 41-41(A)
  bused1 42-42(A)
  bused2 43-43(A)
  bused3 44-44(A)
  bloctype 45-46
  bpremise 47-48(A)
  bntry 49-49(A)
  btype1 50-50(A)
  btype2 51-51(A)
  btype3 52-52(A)
  bweap1 53-54
  bauto1 55-55(A)
  bweap2 56-57
  bauto2 58-58(A)
  bweap3 59-60
  bauto3 61-61(A)
  bhate 62-63.
Record type 3.
data list /
   rdw 1-4 
  action 6-6 (A) 
  month 7-8
  year 9-12
  city 13-16
  ori 17-25 (A)
  incnumb 26-37(A)
  ctyploss 38-38 (a)
  cprodes1 39-40 (a)
  cproval1 41-49 (a)
  crecyr1 50-53
  crecmo1 54-55
  crecday1 56-57
  cprodes2 58-59 (a)
  cproval2 60-68 (a)
  crecyr2 69-72
  crecmo2 73-74
  crecday2 75-76
  cprodes3 77-78 (a)
  cproval3 79-87 (a)
  crecyr3 88-91
  crecmo3 92-93
  crecday3 94-95
  cprodes4 96-97 (a)
  cproval4 98-106 (a)
  crecyr4 107-110
  crecmo4 111-112
  crecday4 113-114
  cprodes5 115-116 (a)
  cproval5 117-125 (a)
  crecyr5 126-129
  crecmo5 130-131
  crecday5 132-133
  cprodes6 134-135 (a)
  cproval6 136-144 (a)
  crecyr6 145-148
  crecmo6 149-150
  crecday6 151-152
  cprodes7 153-154 (a)
  cproval7 155-163(a)
  crecyr7 164-167
  crecmo7 168-169
  crecday7 170-171
  cprodes8 172-173 (a)
  cproval8 174-182 (a)
  crecyr8 183-186
  crecmo8 187-188
  crecday8 189-190
  cprodes9 191-192 (a)
  cproval9 193-201 (a)
  crecyr9 202-205
  crecmo9 206-207
  crecday9 208-209
  cprdes10 210-211 (a)
  cprval10 212-220 (a)
  crecyr10 221-224
  crecmo10 225-226
  crecdy10 227-228
  cstolveh 229-230 
  cstvehre 231-232
  cdrgtpe1 233 (a)
  cdrgqty1 234-242 
  cdrgfra1 243-245 
  cdrgmea1 246-247 (a)
  cdrgtpe2 248 (a)
  cdrgqty2 249-257 
  cdrgfra2 258-260
  cdrgmea2 261-262 (a)
  cdrgtpe3 263 (a)
  cdrgqty3 264-272 
  cdrgfra3 273-275 
  cdrgmea3 276-277 (a)
  coff1 278-280 (a)
  coff2 281-283 (a)
  coff3 284-286 (a)
  coff4 287-289 (a)
  coff5 290-292 (a)
  coff6 293-295 (a)
  coff7 296-298 (a)
  coff8 299-301 (a)
  coff9 302-304 (a)
  coff10 305-307(a).
Record type 4.
data list /
 rdw 1-4 
 level 5-5
 action 6-6 (A)
 month 7-8
 year 9-12
 city 13-16
 ori 17-25 (A)
 incnumb 26-37(A)
 dvctmno 38-40
 doff1 41-43(a)
 doff2 44-46(a)
 doff3 47-49(a)
 doff4 50-52(a)
 doff5 53-55(a)
 doff6 56-58(a)
 doff7 59-61(a)
 doff8 62-64 (a)
 doff9 65-67(a)
 doff10 68-70(a)
 dvcttype 71 (a)
 dage 72-75 (a)
 dsex 76 (a)
 drace 77 (a)
 dthnic 78 (a)
 dResidnt 79 (a)
 dAg_cir1 80-81
 dAg_cir2 82-83 
 dHom_cir 84(a)
 dIn_typ1 85 (a)
 dIn_typ2 86 (a)
 dIn_typ3 87 (a)
 dIn_typ4 88 (a)
 dIn_typ5 89 (a)
 dOf_Rel1 90-91 (a)
 dRelate1 92-93 (a)
 dOf_Rel2 94-95 (a)
 dRelate2 96-97 (a)
 dOf_Rel3 98-99 (a)
 dRelate3 100-101 (a)
 dOf_Rel4 102-103 (a)
 dRelate4 104-105 (a)
 dOf_Rel5 106-107 (a)
 dRelate5 108-109 (a)
 dOf_Rel6 110-111 (a)
 dRelate6 112-113 (a)
 dOf_Rel7 114-115 (a)
 dRelate7 116-117 (a)
 dOf_Rel8 118-119 (a)
 dRelate8 120-121 (a)
 dOf_Rel9 122-123 (a)
 dRelate9 124-125 (a)
 dOf_Re10 126-127 (a)
 dRelat10 128-129 (a)
 dRestime 130-133
 dActaken 134 (a)
 dComplan 135 (a)
 dcall 136 (a)
 dTimes 137-138 (a)
 dPOfile 139 (a)
 dPoviol 140 (a)
 dPofile2 141 (a)
 dTime 142-146 (a)
 dLEOKA1 147 (a)
 dLEOKA2 148-149
 dLEOKA3 150.
Record type 5.
data list /
 rdw 1-4 
 action 6-6 (A) 
 month 7-8
 year 9-12
 city 13-16
 ori 17-25 (A)
 incnumb 26-37(A)
 eoffnumb 38-39
 eage 40-43 (a)
 esex 44 (a)
 erace 45 (a)
 eheight 46-48 (a)
 eeyes 49-51 (a)
 ehair 52-54 (a)
 ehdhair 55
 efhair 57-58 (a)
 eglasses 61
 eoffhand 62
 eskin 63-64 (a)
 eskin2 65-66 (a)
 ebuild 67
 eteeth1 68-69
 eteeth2 70-71
 etattoo1 72-73 (a)
 etattoo2 74-75 (a)
 etatloc1 76-77
 etatloc2 78-79
 escar1 80-81
 escar2 82-83
 espeech1 84-85
 espeech2 86-87
 eid1 88-89
 eid2 90-91.
Record type 6.
data list /
 rdw 1-4 
 action 6-6 (A)
 month 7-8
 year 9-12
 city 13-16
 ori 17-25 (A)
 incnumb 26-37(A)
 arrnum2 38-39
 arrnum1 40-51 (a)
 farryr 52-55
 farrmo 56-57
 farrday 58-59
 farrtype 60 (a)
 farrsegm 61 (a)
 foffcode 62-64 (a)
 fararm1 65-66
 fararm1a 67 (a)
 fararm2 68-69
 fararm2a 70 (a)
 fage 71-74 (a)
 fsex 75 (a)
 frace 76 (a)
 fethn 77 (a)
 fresid 78 (a)
 fdisp 79 (a)
 fclear 80 (a)
 foff1 81-83 (a)
 foff2 84-86 (a)
 foff3 87-89 (a)
 foff4 90-92 (a)
 foff5 93-95 (a)
 foff6 96-98 (a)
 foff7 99-101(a)
 foff8 102-104 (a)
 foff9 105-107 (a)
 foff10 108-110 (a)
 fheight 111-113 (a)
 feyes 114-116 (a)
 fhair 117-119 (a)
 fhdhair1 120
 fhdhair2 121
 ffhair1 122-123
 ffhair2 124-125
 fglass 126
 fhand 127
 fskin1 128-129 (A)
 fskin2 130-131 (a)
 fbuild 132
 fteeth1 133-134
 fteeth2 135-136
 ftattoo1 137-138
 ftattoo2 139-140
 ftatloc1 141-142
 ftatloc2 143-144
 fscar1 145-146
 fscar2 147-148
 fspch1 149-150
 fspch2 151-152
 fid1 153-154
 fid2 155-156.
end file type.

SORT CASES BY ACTION ORI incnumb level.
COMPUTE INC_CNT = 1.
if (ori = lag(ori,1) and incnumb = lag(incnumb,1))
    INC_CNT = LAG(INC_CNT) + 1.
freq INC_CNT.

DO IF (level = 4).
COMPUTE VIC_CNT = 1.
ELSE IF (level = 5).
COMPUTE OFF_CNT = 1.
ELSE IF (level = 6).
COMPUTE ARR_CNT = 1.
END IF.

FREQ VIC_CNT to ARR_CNT.
*************************************************************************
* Prior to aggregating the data we need to define the most serious offense
* in the incident. We will use the victim offense information to define
* the most serious offense. However, before we can define the most serious
* offense we need to recode voff1 to voff10 to numeric variables. This serves
* two purposes. First it reduces the overall size of the file. String variables
* require a minimum of 8 bytes of disk space. If the string is longer than
* eight characters the variable consumes another eight bytes. However, numeric
* variables can be compressed down to one byte regradless of the size of
* the variable. To convert victim offenses to numeric I have created a
* separate syntax file so the conversion can be used for any offense files.
*************************************************************************.
INCLUDE 'n:\syntax files\WVIBRSmsvoff.sps'.
if (sysmis(ainyear))ainyear = lag(ainyear,1).
save outfile = 'n:\new flat files as of 7-07\2005data.sav'/compressed.