Current estimation methods for the probability of causation 'PC' make strong parametric assumptions or are inefficient. We derive a non-parametric influence-function-based estimator for a projection of PC, which allows for simple interpretation and valid inference by making weak structural assumptions. We apply our estimator to real data from an experiment in Kenya. This experiment found, by estimating the average treatment effect, that protecting water springs reduces childhood disease. However, before scaling up this intervention, it is important to determine whether it was the exposure, and not something else, that caused the outcome. Indeed, we find that some children, who were exposed to a high concentration of bacteria in drinking water and had a diarrhoeal disease, would probably have contracted the disease absent the exposure since the estimated PC for an average child in this study is 0.12 with a 95% confidence interval of (0.11, 0.13). Our non-parametric method offers researchers a way to estimate PC, which is essential if we wish to determine not only the average treatment effect, but also whether an exposure probably caused the observed outcome.

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Objectives: In his 2014 Sutherland address to the American Society of Criminology, David Weisburd demonstrated that the share of crime that is accounted for by the most crime-ridden street segments is notably high and strikingly similar across cities, an empirical regularity referred to as the “law of crime concentration.” In the large literature that has since proliferated, there remains considerable debate as to how crime concentration should be measured empirically. We suggest a measure of crime concentration that is simple, accurate and easily interpreted. Methods: Using data from three of the largest cities in the United States, we compare observed crime concentration to a counterfactual distribution of crimes generated by randomizing crimes to street segments. We show that this method avoids a key pitfall that causes a popular method of measuring crime concentration to considerably overstate the degree of crime concentration in a city. Results: While crime is significantly concentrated in a statistical sense and while some crimes are substantively concentrated among hot spots, the precise relationship is considerably weaker than has been documented in the empirical literature. Conclusions: The method we propose is simple and easily interpretable and compliments recent advances which use the Gini coefficient to measure crime concentration.

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Regular proficiency testing of forensic examiners is required at accredited laboratories and widely accepted as an important component of a functioning quality assurance program. Yet, unlike in other testing industries, the majority of forensic laboratories testing programs rely entirely on declared proficiency tests. Some laboratories, primarily federal forensic facilities, have adopted blind proficiency tests, which are also used in the medical and drug testing industries. Blind tests offer advantages. They must resemble actual cases, can test the entire laboratory pipeline, avoid changes in behavior from an examiner knowing they are being tested, and are one of the only methods that can detect misconduct. However, the forensic context present both logistical and cultural obstacles to the implementation of blind proficiency tests. In November 2018, we convened a meeting of directors and quality assurance managers of local and state laboratories to discuss obstacles to the adoption of blind testing and assess successful and potential strategies to overcome them. Here, we compare the situation in forensic science to other testing disciplines, identifying obstacles to the implementation of blind proficiency testing in forensic contexts, and proposing ways to address those issues and increase the ecological validity of proficiency tests at forensic laboratories.

Hal S. Stern, Maria Cuellar and David Kaye describe how scientists define and assess the reliability and validity of some commonly encountered types of forensic science evidence. Such assessments are necessary for courts to admit putatively scientific evidence as bona fide and legally “reliable” science.

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Declared proficiency tests are limited in their use for testing the performance of the entire system, because analysts are aware that they are being tested. A blind quality control (BQC) is intended to appear as a real case to the analyst to remove any intentional or subconscious bias. A BQC program allows a real-time assessment of the laboratory’s policies and procedures and monitors reliability of casework. In September 2015, the Houston Forensic Science Center (HFSC) began a BQC program in blood alcohol analysis. Between September 2015 and July 2018, HFSC submitted 317 blind cases: 89 negative samples and 228 positive samples at five target concentrations (0.08, 0.15, 0.16, 0.20 and 0.25 g/100 mL; theoretical targets). These blood samples were analyzed by a headspace gas chromatograph interfaced with dual-flame ionization detectors (HS-GC-FID). All negative samples produced `no ethanol detected’ results. The mean (range) of reported blood alcohol concentrations (BACs) for the aforementioned target concentrations was 0.075 (0.073–0.078), 0.144 (0.140–0.148), 0.157 (0.155–0.160), 0.195 (0.192–0.200) and 0.249 (0.242–0.258) g/100 mL, respectively. The average BAC percent differences from the target for the positive blind cases ranged from −0.4 to −6.3%, within our uncertainty of measurement (8.95–9.18%). The rate of alcohol evaporation/degradation was determined negligible. A multiple linear regression analysis was performed to compare the % difference in BAC among five target concentrations, eight analysts, three HS-GC-FID instruments and two pipettes. The variables other than target concentrations showed no significant difference (P > 0.2). While the 0.08 g/100 mL target showed a significantly larger % difference than higher target concentrations (0.15–0.25 g/100 mL), the % differences among the higher targets were not concentration-dependent. Despite difficulties like gaining buy-in from stakeholders and mimicking evidence samples, the implementation of a BQC program has improved processes, shown methods are reliable and added confidence to staff’s testimony in court.