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The chance that a person experiences an event (a first arrest, a first conviction, a first jail stay, a first child protection placement) by each age, from first events and the population by age, as a synthetic cohort; with mortality as a competing risk when deaths are given.

Usage

cmlrisk(age, fireve, pop, atrisk = NULL, dthrate = NULL, conflvl = 0.95)

Arguments

age

The ages, in order.

fireve

First events at each age.

pop

The population at each age.

atrisk

Optional: the persons at risk at each age, when known, in place of the synthetic-cohort assumption.

dthrate

Optional death rates by age (probability of dying within the age).

conflvl

Confidence level of the cumulative risk limits (default 0.95).

Value

A data frame of class rmbl_cumrisk: age, hazard, atrisk, cmlrisk, lower, upper.

Details

With \(E_a\) first events at age \(a\) and \(N_a\) persons at risk (those who have not had the event), the hazard is \(h_a = E_a/N_a\). When only the population \(P_a\) is known, the persons at risk are taken as \(P_a(1 - CR_{a-1})\) (the synthetic-cohort assumption). Without mortality, \(CR_a = 1 - \prod_{x \le a}(1 - h_x)\). With death rates \(q_x\), the multiple-decrement table carries survivors \(l_{x+1} = l_x(1 - h_x - q_x)\) and \(CR_a = \sum_{x \le a} l_x h_x / l_0\), the risk of the event before death. The interval (without mortality) is Greenwood's on the log of the survival: \(\mathrm{Var}(\log S_a) = \sum_{x \le a} h_x/(N_x(1 - h_x))\).

Counting first events needs records that link a person's events over time; an agency's counts of all events overstate first events. Events of people who do not live in the area, counted against its population, bias the risk upward.

References

Bonczar TP (2003). Prevalence of imprisonment in the U.S. population, 1974-2001. Bureau of Justice Statistics, NCJ 197976.

Applied to arrests, convictions and jail in New York City: Hepburn P, Kohler-Hausmann I, Zorro Medina A (2019). Cumulative risks of multiple criminal justice outcomes in New York City. Demography 56(3):1161-1171. doi:10.1007/s13524-019-00781-7

Examples

age <- 16:25
first <- c(900, 1400, 1700, 1600, 1400, 1100, 900, 700, 600, 500)
pop <- rep(100000, 10)
cmlrisk(age, first, pop)
#> ╭── Cumulative risk of a first event ─────────────────────────────────╮
#> │   Ages                  16 to 25                                    │
#> │   Risk by the last age  10.8% [10.6, 11.0]                          │
#> │                                                                     │
#> │   age   hazard   atrisk  cumrisk  interval                          │
#> │   ---  -------  -------  -------  ------------------                │
#> │    16  0.00900  100,000  0.00900  [0.00841, 0.00959]                │
#> │    17  0.01413   99,100  0.02300  [0.02207, 0.02393]                │
#> │    18  0.01740   97,700  0.04000  [0.03878, 0.04121]                │
#> │    19  0.01667   96,000  0.05600  [0.05457, 0.05742]                │
#> │    20  0.01483   94,400  0.07000  [0.06842, 0.07158]                │
#> │    21  0.01183   93,000  0.08100  [0.07931, 0.08269]                │
#> │    22  0.00979   91,900  0.09000  [0.08822, 0.09177]                │
#> │    23  0.00769   91,000  0.09700  [0.09516, 0.09883]                │
#> │    24  0.00664   90,300  0.10300  [0.10111, 0.10488]                │
#> │    25  0.00557   89,700  0.10800  [0.10607, 0.10992]                │
#> │                                                                     │
#> │   By age 25 an estimated 10.8% of the population have had a first   │
#> │   event, from the age-specific first-event hazards of a life table. │
#> ╰─────────────────────────────────────────────────────────────────────╯