Time To Rearrest Survival Quartile Estimator

Invert existing Kaplan-Meier product-limit steps to actual rearrest cohort 25/50/75 percent event quantile times, retaining unreached−1and censoring. Event/censor ties use existing estimator; not an individual risk forecast or treat rearrest as conviction.

Description

Rearrest follow-up may end without an observed event, creating right-censored records.

Rearrest follow-up may end without an observed event, creating right-censored records.^[1]

Product-limit estimates account for this when locating observed event-time quartiles. Use this tool to calculate the stated observation or conditional model from supplied measurements.

When to use Time To Rearrest Survival Quartile Estimator

Use this tool to calculate the stated observation or conditional model from supplied measurements. Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.

How to use Time To Rearrest Survival Quartile Estimator and understand its results

Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.
Enter independentlyObservedFollowupTimes, independentlyVerifiedRearrestEventFlags, using the field meanings and rules below, then run the tool.
Read result.observedProductLimitQuartileTimes, result.quartileReachedFlags. Interpret each field using the units, signs and evidence rules below.
If input validation fails, correct the reported field and run again. Before applying a successful result, check the stated reference scope, units, assumptions and any retained unknown evidence.

Input field	Meaning	Value type	Requirement
independentlyObservedFollowupTimes	Independently observed followup times	list of number	Required
independentlyVerifiedRearrestEventFlags	Independently verified rearrest event flags; binary 0/1 in the order documented below	list of number	Required

Supply nonempty aligned nonnegative follow-up times and binary rearrest-event flags, with 0 representing right censoring. Sort by time; group ties with events evaluated against the risk set before any tied records leave it. Multiply survival by 1−events/atRisk at each event time and round stored survival to 12 significant digits. For thresholds 0.75, 0.5 and 0.25 in that order, select the first event time with stored survival≤threshold. Return −1 and reached flag 0 when a threshold is not reached; these are unavailable quartiles, not negative follow-up times.^[2]

S(t)=product_over_event_times(1−eventsAtTime/atRiskAtTime); quartileTimes=first t where S(t)≤[0.75,0.50,0.25], else−1

Apply the field units and exact ordering, boundary and evidence rules above.

Output field	Meaning	Value type
result	Structured result containing the calculation or selected reference fields below	object
result.observedProductLimitQuartileTimes	Times at first survival crossings 0.75, 0.5 and 0.25, in that order; −1 for an unreached threshold	list of number
result.quartileReachedFlags	Per-quartile 1 when its time is reached, otherwise 0	list of number

json

{
  "input": {
    "independentlyObservedFollowupTimes": [
      1,
      2,
      3,
      4
    ],
    "independentlyVerifiedRearrestEventFlags": [
      1,
      1,
      1,
      1
    ]
  },
  "output": {
    "result": {
      "observedProductLimitQuartileTimes": [
        1,
        2,
        3
      ],
      "quartileReachedFlags": [
        1,
        1,
        1
      ]
    }
  }
}

Limitations and assumptions

Product-limit estimates account for this when locating observed event-time quartiles. Results depend on the independently established measurement basis and the exact model assumptions above.

Every listed input requires an explicit value. Unexpected fields, incorrect value types, nonfinite numbers and sparse numeric arrays fail validation; tool-specific bounds and alignment rules apply as described above. Extremely large inputs or outputs can also be rejected. An input error is distinct from a successful calculation that reports a false comparison or retains unknown evidence.

Alternative or Complementary methods

Use Recidivism Three Year BJS Baseline Lookup to examine a related aspect: A recidivism baseline belongs to a specified release cohort, outcome and follow-up period.

Use Desistance Hazard Halfway Age Lookup where its separate inputs and scope apply: Desistance hazard estimates depend on event definitions, cohorts and censoring.

References

Time To Rearrest Survival Quartile Estimator — tool.io
Implementation helper: statistics/kaplan-meier — tool.io

Similar or alternative tools

Recidivism Three Year BJS Baseline Lookup
A recidivism baseline belongs to a specified release cohort, outcome and follow-up period.
Desistance Hazard Halfway Age Lookup
Desistance hazard estimates depend on event definitions, cohorts and censoring.