The Impact of Socioeconomic Factors on State Suicide Rates: Revisited

This paper revisits the purported impact of socioeconomic and social environment factors on annual, U.S. state-level suicide rates. Special attention is paid to the right-hand-side linking covariates directly to Durkheim's (1897/1951) significant contributions to established ecological suicide research. Results from a Haus-man-Taylor panel specification lend little support to Durkheim's social integra-tion/regulation hypothesis that aggregate social forces matter in explaining varia-tions in regional suicide rates. Data from 1990-2019 and the advanced empirical method support the mounting sentiment of an abiding ecological fallacy plaguing suicidology. JEL classification numbers: C51, R11, I31. Keywords: Hausman-Taylor, Suicide rates, Socioeconomic factors.

The Weight of Evidence

Courts of law must weigh evidence to determine the likelihood of competing interpretations of past events, and different legal contexts require different standards of proof, but this falls short of a quantification of probability. Bayes’s theorem and the associated formula provide a way of combining multiple elements of evidence and using them to refine prior assessments of probability. The prosecutor’s fallacy involves an incorrect reversal of the logic of evidence. The ecological fallacy involves incorrectly attributing proportions derived from large groups to smaller groups or individuals.

Most published meta-regression analyses based on aggregate data suffer from methodological pitfalls: a meta-epidemiological study

Background Due to clinical and methodological diversity, clinical studies included in meta-analyses often differ in ways that lead to differences in treatment effects across studies. Meta-regression analysis is generally recommended to explore associations between study-level characteristics and treatment effect, however, three key pitfalls of meta-regression may lead to invalid conclusions. Our aims were to determine the frequency of these three pitfalls of meta-regression analyses, examine characteristics associated with the occurrence of these pitfalls, and explore changes between 2002 and 2012. Methods A meta-epidemiological study of studies including aggregate data meta-regression analysis in the years 2002 and 2012. We assessed the prevalence of meta-regression analyses with at least 1 of 3 pitfalls: ecological fallacy, overfitting, and inappropriate methods to regress treatment effects against the risk of the analysed outcome. We used logistic regression to investigate study characteristics associated with pitfalls and examined differences between 2002 and 2012. Results Our search yielded 580 studies with meta-analyses, of which 81 included meta-regression analyses with aggregated data. 57 meta-regression analyses were found to contain at least one pitfall (70%): 53 were susceptible to ecological fallacy (65%), 14 had a risk of overfitting (17%), and 5 inappropriately regressed treatment effects against the risk of the analysed outcome (6%). We found no difference in the prevalence of meta-regression analyses with methodological pitfalls between 2002 and 2012, nor any study-level characteristic that was clearly associated with the occurrence of any of the pitfalls. Conclusion The majority of meta-regression analyses based on aggregate data contain methodological pitfalls that may result in misleading findings.

Evaluations of science are robustly biased by identity concerns

People are known to evaluate science based on whether it (dis)affirms their collective identities. We examined whether personal identity concerns also bias evaluation processes by manipulating the degree to which summaries of ostensible scientific research about an unfamiliar topic manipulating whether summaries were or inconsistent with how participants thought about themselves. In three preregistered experiments ( N = 644) conducted across two continents, participants were more likely to believe the science when its conclusions aligned with prior understanding of their self, effects that were mediated through positive emotional reactions. Two of the experiments also tested a de-biasing intervention: prior to evaluating science, participants received a brief tutorial on the ecological fallacy (of which, self-related biases represent a special case). The tutorial did not mitigate identity-biased evaluations. This experimental evidence raises questions about whether it is possible to engage global citizens more fully in science consumption while not further triggering identity-based biasing processes.

Predictive Role of Population Density and Use of Public Transport for Major Outcomes of SARS-CoV-2 Infection in the Italian Population: An Ecological Study

Background: This study aimed at assessing how population density (PD), aging index (AI), use of public transport (URPT), and PM10 concentration (PI) modulated the trajectory of the main COVID-19 pandemic outcomes in Italy, also in the recrudescence phase of the epidemic. Study design: Ecological study. Methods: For each region, we recovered data about cases, deaths, and case fatality rate (CFR) recorded since both the beginning of the epidemic and September 1, 2020. Data about total hospitalizations were included as well. Results: PD correlated with, and was the best predictor of, total and partial cases, total and partial deaths, and total hospitalizations. Moreover, URPT correlated with, and was the best predictor of, total CFR. Besides, PI correlated significantly with total and partial cases, total and partial deaths, and total hospitalizations. Conclusions: PD explains COVID-19 morbidity, mortality, and severity while URPT is the best predictor of disease lethality. These findings should be interpreted with caution due to the ecological fallacy.