Repeat Victimization Within Year Flag Checker

Observed repeat victimization within caller established[0, year-end) day window, distinct events and stable pseudonymous victim IDs. Unknown/unreported incidents absent; no individual future risk inference.

Description

Repeat victimization requires distinct recorded events linked to the same adopted victim identifier.

Repeat victimization requires distinct recorded events linked to the same adopted victim identifier.^[1]

The time window and identity-linking basis determine which events count. Use this tool to calculate the stated observation or conditional model from supplied measurements.

When to use Repeat Victimization Within Year Flag Checker

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 Repeat Victimization Within Year Flag Checker and understand its results

Establish the jurisdiction or research scope, observation and event definitions, reference date, matched period and denominator basis.
Enter callerEventIds, callerVictimIds, independentlyRecordedDayOffsets, callerYearEndExclusive, using the field meanings and rules below, then run the tool.
Read result.repeatObservedVictimIds, result.outsideWindowEventIds. 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
callerEventIds	Caller event ids	list of string	Required
callerVictimIds	Caller victim ids	list of string	Required
independentlyRecordedDayOffsets	Independently recorded day offsets	list of number	Required
callerYearEndExclusive	Caller year end exclusive	number	Required

Require nonempty unique nonblank event IDs and aligned nonblank victim IDs and nonnegative finite day offsets. Victim IDs may repeat. Require a positive year-end-exclusive offset. Count events with offset<end for each exact victim ID and return victims with at least two included events, in first-seen order. Return event IDs at or beyond the end separately. Fractional offsets and externally defined year duration are allowed.

repeatVictims={id:count(events with matching id and 0≤dayOffset<endExclusive)≥2}; outsideEvents={event_i:dayOffset_i≥endExclusive}

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.repeatObservedVictimIds	Repeat Observed Victim Ids; use the units, sign convention and calculation stated above	list of string
result.outsideWindowEventIds	Outside Window Event Ids; use the units, sign convention and calculation stated above	list of string

json

{
  "input": {
    "callerEventIds": [
      "e1",
      "e2",
      "e3"
    ],
    "callerVictimIds": [
      "a",
      "a",
      "b"
    ],
    "independentlyRecordedDayOffsets": [
      0,
      10,
      365
    ],
    "callerYearEndExclusive": 365
  },
  "output": {
    "result": {
      "repeatObservedVictimIds": [
        "a"
      ],
      "outsideWindowEventIds": [
        "e3"
      ]
    }
  }
}

Limitations and assumptions

The time window and identity-linking basis determine which events count. 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 Victim Offender Relationship Classifier Lookup to examine a related aspect: Victim–offender relationship categories belong to a specific statistical or survey scheme.

Use Indirect Household vs Personal Victim Classifier where its separate inputs and scope apply: Personal and household victimization are different observation levels.

References

Repeat Victimization Within Year Flag Checker — tool.io

Similar or alternative tools

Victim Offender Relationship Classifier Lookup
Victim–offender relationship categories belong to a specific statistical or survey scheme.
Indirect Household vs Personal Victim Classifier
Personal and household victimization are different observation levels.