Statistical reproducibility of meta-analysis research claims for medical mask use in community settings to prevent COVID infection

The coronavirus pandemic (COVID) has been an exceptional test of current scientific evidence that inform and shape policy. Many US states, cities, and counties implemented public orders for mask use on the notion that this intervention would delay and flatten the epidemic peak and largely benefit public health outcomes. P-value plotting was used to evaluate statistical reproducibility of meta-analysis research claims of a benefit for medical (surgical) mask use in community settings to prevent COVID infection. Eight studies (seven meta-analyses, one systematic review) published between 1 January 2020 and 7 December 2022 were evaluated. Base studies were randomized control trials with outcomes of medical diagnosis or laboratory-confirmed diagnosis of viral (Influenza or COVID) illness. Self-reported viral illness outcomes were excluded because of awareness bias. No evidence was observed for a medical mask use benefit to prevent viral infections in six p-value plots (five meta-analyses and one systematic review). Research claims of no benefit in three meta-analyses and the systematic review were reproduced in p-value plots. Research claims of a benefit in two meta-analyses were not reproduced in p-value plots. Insufficient data were available to construct p-value plots for two meta-analyses because of overreliance on self-reported outcomes. These findings suggest a benefit for medical mask use in community settings to prevent viral, including COVID infection, is unproven.Comment: 21 pages, 100 references, 3 appendice

Statistical reliability of meta_analysis research claims for gas stove cooking_childhood respiratory health associations

Odds ratios or p_values from individual observational studies can be combined to examine a common cause_effect research question in meta_analysis. However, reliability of individual studies used in meta_analysis should not be taken for granted as claimed cause_effect associations may not reproduce. An evaluation was undertaken on meta_analysis of base papers examining gas stove cooking, including nitrogen dioxide, NO2, and childhood asthma and wheeze associations. Numbers of hypotheses tested in 14 of 27 base papers, 52 percent, used in meta_analysis of asthma and wheeze were counted. Test statistics used in the meta_analysis, 40 odds ratios with 95 percent confidence limits, were converted to p_values and presented in p_value plots. The median and interquartile range of possible numbers of hypotheses tested in the 14 base papers was 15,360, 6,336_49,152. None of the 14 base papers made mention of correcting for multiple testing, nor was any explanation offered if no multiple testing procedure was used. Given large numbers of hypotheses available, statistics drawn from base papers and used for meta-analysis are likely biased. Even so, p-value plots for gas stove_current asthma and gas stove_current wheeze associations show randomness consistent with unproven gas stove harms. The meta-analysis fails to provide reliable evidence for public health policy making on gas stove harms to children in North America. NO2 is not established as a biologically plausible explanation of a causal link with childhood asthma. Biases_multiple testing and p-hacking_cannot be ruled out as explanations for a gas stove_current asthma association claim. Selective reporting is another bias in published literature of gas stove_childhood respiratory health studies. Keywords gas stove, asthma, meta-analysis, p-value plot, multiple testing, p_hackingComment: International Journal of Statistics and Probability (2023

Sustainable Mobility for Rural Small University Towns

How can all of the emerging changes in transportation affect a small rural University town? This panel will discuss the opportunities and the drawbacks to automated vehicles, shared vehicles, electric, and solar powered vehicles. The panel will be comprised of various academics and professionals involved with these new transportation changes

LocalControl: An R Package for Comparative Safety and Effectiveness Research

The LocalControl R package implements novel approaches to address biases and confounding when comparing treatments or exposures in observational studies of outcomes. While designed and appropriate for use in comparative safety and effectiveness research involving medicine and the life sciences, the package can be used in other situations involving outcomes with multiple confounders. LocalControl is an open-source tool for researchers whose aim is to generate high quality evidence using observational data. The package implements a family of methods for non-parametric bias correction when comparing treatments in observational studies, including survival analysis settings, where competing risks and/or censoring may be present. The approach extends to bias-corrected personalized predictions of treatment outcome differences, and analysis of heterogeneity of treatment effect-sizes across patient subgroups

Evaluation of Special Event Traffic Management: The Brickyard 400 Case Study

This paper reports on the anonymous tracking of Bluetooth enabled consumer electronic devices to measure the travel time, or space mean speed, of travelers. This sampling technique was deployed at six interstate locations and two signalized arterials in the Indianapolis, IN metropolitan area the week of the NASCAR Brickyard 400. The week prior to the race before data was also collected from a subset of those sites. The day of the race, almost 19,000 unique MAC address were captured at the eight locations. From that information real-time travel time estimates were provided to Indiana Department of Transportation (INDOT) mobile data terminals. After the race, the data was processed to obtain travel time plots and origin destination matrixes to provide a quantitative evaluation of race day traffic management operations. Selected reports and charts from that analysis are discussed in the paper

The Effects of Silicone Contamination on Bond Performance of Various Bond Systems

The sensitivity to silicone contamination of a wide variety of adhesive bond systems is discussed. Generalizations regarding factors that make some bond systems more sensitive to contamination than others are inferred and discussed. The effect of silane adhesion promoting primer on the contamination sensitivity of two epoxy/steel bond systems is also discussed