jefftk comments on How Risky Is Trick-or-Treating?

[jefftk]

1: while the data is supposed to include all traffic fatalities, it includes few injuries, and in recent data it only includes fatalities

2: I don’t see that in the data:

$ head -n 1 2020/person.csv | tr ',' '\n' | cat -n
     1	STATE
     2	STATENAME
     3	ST_CASE
     4	VE_FORMS
     5	VEH_NO
     6	PER_NO
     7	STR_VEH
     8	COUNTY
     9	DAY
    10	DAYNAME
    11	MONTH
    12	MONTHNAME
    13	HOUR
    14	HOURNAME
    15	MINUTE
    16	MINUTENAME
    17	RUR_URB
    18	RUR_URBNAME
    19	FUNC_SYS
    20	FUNC_SYSNAME
    21	HARM_EV
    22	HARM_EVNAME
    23	MAN_COLL
    24	MAN_COLLNAME
    25	SCH_BUS
    26	SCH_BUSNAME
    27	MAKE
    28	MAKENAME
    29	MAK_MOD
    30	BODY_TYP
    31	BODY_TYPNAME
    32	MOD_YEAR
    33	MOD_YEARNAME
    34	TOW_VEH
    35	TOW_VEHNAME
    36	SPEC_USE
    37	SPEC_USENAME
    38	EMER_USE
    39	EMER_USENAME
    40	ROLLOVER
    41	ROLLOVERNAME
    42	IMPACT1
    43	IMPACT1NAME
    44	FIRE_EXP
    45	FIRE_EXPNAME
    46	AGE
    47	AGENAME
    48	SEX
    49	SEXNAME
    50	PER_TYP
    51	PER_TYPNAME
    52	INJ_SEV
    53	INJ_SEVNAME
    54	SEAT_POS
    55	SEAT_POSNAME
    56	REST_USE
    57	REST_USENAME
    58	REST_MIS
    59	REST_MISNAME
    60	AIR_BAG
    61	AIR_BAGNAME
    62	EJECTION
    63	EJECTIONNAME
    64	EJ_PATH
    65	EJ_PATHNAME
    66	EXTRICAT
    67	EXTRICATNAME
    68	DRINKING
    69	DRINKINGNAME
    70	ALC_DET
    71	ALC_DETNAME
    72	ALC_STATUS
    73	ALC_STATUSNAME
    74	ATST_TYP
    75	ATST_TYPNAME
    76	ALC_RES
    77	ALC_RESNAME
    78	DRUGS
    79	DRUGSNAME
    80	DRUG_DET
    81	DRUG_DETNAME
    82	DSTATUS
    83	DSTATUSNAME
    84	HOSPITAL
    85	HOSPITALNAME
    86	DOA
    87	DOANAME
    88	DEATH_DA
    89	DEATH_DANAME
    90	DEATH_MO
    91	DEATH_MONAME
    92	DEATH_YR
    93	DEATH_YRNAME
    94	DEATH_HR
    95	DEATH_HRNAME
    96	DEATH_MN
    97	DEATH_MNNAME
    98	DEATH_TM
    99	DEATH_TMNAME
   100	LAG_HRS
   101	LAG_HRSNAME
   102	LAG_MINS
   103	LAG_MINSNAME
   104	WORK_INJ
   105	WORK_INJNAME
   106	HISPANIC
   107	HISPANICNAME
   108	LOCATION
   109	LOCATIONNAME
   110	HELM_USE
   111	HELM_USENAME
   112	HELM_MIS
   113	HELM_MISNAME
   114	VPICMAKE
   115	VPICMAKENAME
   116	VPICMODEL
   117	VPICMODELNAME
   118	VPICBODYCLASS
   119	VPICBODYCLASSNAME
   120	ICFINALBODY
   121	ICFINALBODYNAME

[braces]

You can get the age of the driver by looking at the age of the person with PER_TYP equal to one.

[jefftk]

I’m not that familiar with the data, but how would I link that record to a child death?

[braces]

Within years, the combo of ST_CASE and STATE uniquely identifies accidents, so an intermediate step is tracking the accident ID. Then you could classify accidents as involving a child as those where at least one of the decedents is under a certain age, then use that PER_TYP variable to look at the ages of the driver(s) for those accidents. Cool analysis, btw—I’ve worked a lot with the FARS and happy to help :)