Inference without randomization or ignorability: A stability­ controlled quasi-experiment on the prevention of tuberculosis

When determining the effectiveness of a new treatment, randomized trials are not always possible or desirable. The stability-controlled quasi-experiment (SCQE) (Hazlett, 2019) is an observational approach that replaces the usual “no-unobserved confounding” assumption with one on the change in non-treatment outcome between successive cohorts, or the “baseline trend.” We extend this method to allow variance estimation and inference, and apply it for the first time by examining whether isoniazid preventive therapy (IPT) reduced tuberculosis (TB) incidence among 26,715 HIV patients in Tanzania. After IPT became available in the clinics we studied, a non-random 25% of patients received it. Within a year, fewer than 1% of patients on IPT developed TB, compared to 16% of the untreated. Regression adjustment using available covari-ates produces an equally large and highly significant estimate of -15 percentage point (pp) [95%CI: -16.6, -13.7]. While those estimates may generate confidence in IPT’s effectiveness, they cannot eliminate confounding. By contrast, SCQE reveals that the average treatment effect on the treated must be small and indistinguishable from zero, if we assume the baseline trend was flat over the study period. Rather, to argue that IPT was beneficial requires claiming that the (non-treatment) incidence rate rose by at least 0.5 pp per year. This is plausible, but far from certain. The SCQE approach has broad applicability and will sometimes lead to definitive claims of effectiveness. In this case, it usefully aids in protecting against over-confidence in claims that IPT was effective

Causal progress with imperfect placebo treatments and outcomes

In the quest to make defensible causal claims from observational data, it is sometimes possible to leverage information from "placebo treatments" and "placebo outcomes" (or "negative outcome controls"). Existing approaches employing such information focus largely on point identification and assume (i) "perfect placebos", meaning placebo treatments have precisely zero effect on the outcome and the real treatment has precisely zero effect on a placebo outcome; and (ii) "equiconfounding", meaning that the treatment-outcome relationship where one is a placebo suffers the same amount of confounding as does the real treatment-outcome relationship, on some scale. We instead consider an omitted variable bias framework, in which users can postulate non-zero effects of placebo treatment on real outcomes or of real treatments on placebo outcomes, and the relative strengths of confounding suffered by a placebo treatment/outcome compared to the true treatment-outcome relationship. Once postulated, these assumptions identify or bound the linear estimates of treatment effects. While applicable in many settings, one ubiquitous use-case for this approach is to employ pre-treatment outcomes as (perfect) placebo outcomes. In this setting, the parallel trends assumption of difference-in-difference is in fact a strict equiconfounding assumption on a particular scale, which can be relaxed in our framework. Finally, we demonstrate the use of our framework with two applications, employing an R package that implements these approaches

Threat perceptions, loyalties and attitudes towards peace: The effects of civilian victimization among Syrian refugees in Turkey

For refugees who have fled civil conflict, do experiences of victimization by one armed group push them to support the opposing armed groups? Or, does victimization cause refugees to revoke their support for all armed groups, whatever side they are on, and call instead for peace? This paper studies the effect of civilian victimization on threat perceptions, loyalties, and attitudes toward peace in the context of Syrian refugees in Turkey, many of whom faced regime-caused violence prior to their departure. Our research strategy leverages variation in home destruction caused by barrel bombs to examine the effect of violence on refugees’ views. We find that refugees who lose their home to barrel bombs withdraw support from armed actors and are more supportive of ending the war and finding peace. Suggestive evidence shows that while victims do not disengage from issues in Syria, they do show less optimism about an opposition victory

Real Effect or Bias? Best Practices for Evaluating the Robustness of Real-World Evidence through Quantitative Sensitivity Analysis for Unmeasured Confounding

The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is likely in part due to complexity of implementation and often specific and restrictive data requirements required for application of each method. With the advent of sensitivity analyses methods that are broadly applicable in that they do not require identification of a specific unmeasured confounder, along with publicly available code for implementation, roadblocks toward broader use are decreasing. To spur greater application, here we present a best practice guidance to address the potential for unmeasured confounding at both the design and analysis stages, including a set of framing questions and an analytic toolbox for researchers. The questions at the design stage guide the research through steps evaluating the potential robustness of the design while encouraging gathering of additional data to reduce uncertainty due to potential confounding. At the analysis stage, the questions guide researchers to quantifying the robustness of the observed result and providing researchers with a clearer indication of the robustness of their conclusions. We demonstrate the application of the guidance using simulated data based on a real-world fibromyalgia study, applying multiple methods from our analytic toolbox for illustration purposes.Comment: 16 pages which includes 5 figure

Early Brain Overgrowth in Autism Associated With an Increase in Cortical Surface Area Before Age 2 Years

Brain enlargement has been observed in 2 year old children with autism but the underlying mechanisms are unknown. This longitudinal MRI study investigated early growth trajectories in brain volume and cortical thickness

A Persuasive Peace: Syrian Refugees' Attitudes Towards Compromise and Civil War Termination

Civilians who have fled violent conflict and settled in neighboring countries are integral to processes of civil war termination. Contingent on their attitudes, they can either back peaceful settlements or support warring groups and continued fighting. Attitudes toward peaceful settlement are expected to be especially obdurate for civilians who have been exposed to violence. In a survey of 1,120 Syrian refugees in Turkey conducted in 2016, we use experiments to examine attitudes towards two critical phases of conflict termination – a ceasefire and a peace agreement. We examine the rigidity/flexibility of refugees’ attitudes to see if subtle changes in how wartime losses are framed or in who endorses a peace process can shift willingness to compromise with the incumbent Assad regime. Our results show, first, that refugees are far more likely to agree to a ceasefire proposed by a civilian as opposed to one proposed by armed actors from either the Syrian government or the opposition. Second, simply describing the refugee community’s wartime experience as suffering rather than sacrifice substantially increases willingness to compromise with the regime to bring about peace. This effect remains strong among those who experienced greater violence. Together, these results show that even among a highly pro-opposition population that has experienced severe violence, willingness to settle and make peace are remarkably flexible and dependent upon these cues