Analysis of residuals in contingency tables: another nail in the coffin of conditional approaches to significance testing.

Omnibus tests of significance in contingency tables use statistics of the chi-square type. When the null is rejected, residual analyses are conducted to identify cells in which observed frequencies differ significantly from expected frequencies. Residual analyses are thus conditioned on a significant omnibus test. Conditional approaches have been shown to substantially alter type I error rates in cases involving t tests conditional on the results of a test of equality of variances, or tests of regression coefficients conditional on the results of tests of heteroscedasticity. We show that residual analyses conditional on a significant omnibus test are also affected by this problem, yielding type I error rates that can be up to 6 times larger than nominal rates, depending on the size of the table and the form of the marginal distributions. We explored several unconditional approaches in search for a method that maintains the nominal type I error rate and found out that a bootstrap correction for multiple testing achieved this goal. The validity of this approach is documented for two-way contingency tables in the contexts of tests of independence, tests of homogeneity, and fitting psychometric functions. Computer code in MATLAB and R to conduct these analyses is provided as Supplementary Material.

Emotional Theory of Rationality

In recent decades, it has been definitely established the existence of a close relationship between the emotional phenomena and rational processes, but we still do not have a unified definition, or effective models to describe any of them well. To advance our understanding of the mechanisms governing the behavior of living beings we must integrate multiple theories, experiments and models from both fields. In this paper we propose a new theoretical framework that allows integrating and understanding, from a functional point of view, the emotion-cognition duality. Our reasoning, based on evolutionary principles, add to the definition and understanding of emotion, justifying its origin, explaining its mission and dynamics, and linking it to higher cognitive processes, mainly with attention, cognition, decision-making and consciousness. According to our theory, emotions are the mechanism for brain function optimization, besides being the contingency and stimuli prioritization system. As a result of this approach, we have developed a dynamic systems-level model capable of providing plausible explanations for some psychological and behavioral phenomena, and establish a new framework for scientific definition of some fundamental psychological terms.

Ecology of antimicrobial resistance: humans, animals, food and environment

Antimicrobial resistance is a major health problem. After decades of research, numerous difficulties in tackling resistance have emerged, from the paucity of new antimicrobials to the inefficient contingency plans to reduce the use of antimicrobials; consequently, resistance to these drugs is out of control. Today we know that bacteria from the environment are often at the very origin of the acquired resistance determinants found in hospitals worldwide. Here we define the genetic components that flow from the environment to pathogenic bacteria and thereby confer a quantum increase in resistance levels, as resistance units (RU). Environmental bacteria as well as microbiomes from humans, animals, and food represent an infinite reservoir of RU, which are based on genes that have had, or not, a resistance function in their original bacterial hosts. This brief review presents our current knowledge of antimicrobial resistance and its consequences, with special focus on the importance of an ecologic perspective of antimicrobial resistance. This discipline encompasses the study of the relationships of entities and events in the framework of curing and preventing disease, a definition that takes into account both microbial ecology and antimicrobial resistance. Understanding the flux of RU throughout the diverse ecosystems is crucial to assess, prevent and eventually predict emerging scaffolds before they colonize health institutions. Collaborative horizontal research scenarios should be envisaged and involve all actors working with humans, animals, food and the environment.