This is an outline of The TRACE Technique (Threat assessment, Reconciliation with facts, Analysis of competing explanations, Conditional probability Evaluation), an analytical methodology developed collaboratively by AI and this analyst to examine the disappearance of Amy Wroe Bechtel. It is applicable to any criminal case with minimal physical evidence. TRACE shifts the focus of the analysis away from what, why, or how something happened, to which hypothesis best reconciles with known facts or evidence patterns, and then factors in probability, opportunity, and logistics. See the Amy Wroe Bechtel case for an example of its application.
PHASE 1: Hypothesis Generation
Consider a wide range of possible explanations based on the circumstances of the case.
Phase 2: Reconciliation with facts
- Base rate research: How often does each scenario actually occur in similar circumstances? Consider statistical frequency, comparable cases, regional/environmental factors.
- Case-specific facts: What do we know with certainty about this incident? Consider timeline precision, location characteristics, victim profile and behavior patterns, relationship context, physical evidence (if any).
- Evidence expectations: For each hypothesis, what physical evidence should exist if this scenario occurred?
Phase 3: Analysis of Competing Explanations
- Evidence signature match (ESM): Does the evidence pattern at the scene match what this hypothesis should produce? Scale: Yes=1, No=-1
- Opportunity/feasibility (O/F): Was this scenario physically possible given time, location, and circumstances? Consider timeline constraints; location; access; victim behavior patterns. Scale: 1-10 (1 being least feasible; 10 being most feasible)
- Logistical complexity (LC): Could the event have happened naturally in place, and in the absence of evidence (low complexity = 1 [more likely]), or did the event require cleaning or staging, which increases the likelihood of evidence left behind (high complexity = -1 [less likely])
- Elimination factors (EF): Are there specific facts that rule out or severely undermine this hypothesis? (strongly undermine = -2; undermine = -1; neutral = 0)
PHASE 4: Conditional Probability Evaluation
Fill in the matrix with your results. (See here for an example of a completed matrix.)
| ESM (Yes = 1; No = -1 | O/F (1-10) | LC (Low = 1; High = -1 | EF (strongly undermine = -2; undermine = -1; neutral = 0) | STRENGTH SCORE | |
| H1 | |||||
| H2 | |||||
| H3-, … |
Phase 5: Outcome
Higher scores more closely fit the evidence pattern; lower scores can be effectively eliminated unless additional facts arise in the course of the investigation. Present your hypotheses in order of likelihood and explain why they scored the way they did. Frame your argument around the four elements of the Analysis of Competing Explanations section: evidence signature match, opportunity/feasibility; logistical complexity, elimination factors.