Distinguishing the Ratio Bias from Unsystematic Error: Situation and Individual‐difference Effects

People often perceive the occurrence of events to be less likely when the likelihood of the event is expressed in ratios consisting of smaller numbers versus larger numbers, an effect known as the ratio bias. This work presents a theoretical framework for the conditions that need to be met for the ratio bias to occur. In doing so, we contrast effects on the ratio bias to those on unsystematic error, which have often been confounded in previous research. We find that the ratio bias is weaker (1) when both sets of numbers are relatively large than when both sets of numbers are relatively small; (2) for scenarios involving lottery tickets than for scenarios involving drawing balls from a bin; and (3) when a physical display depicting the numbers is provided to participants. Each of these factors reduced the ratio bias without reducing unsystematic error. Additionally, we show that unsystematic error is lower among people who (1) reason on the basis of proportions rather than on the basis of the numerator and denominator individually; (2) score higher on the rational scale of the Rational–Experiential Inventory; and (3) are of higher numeracy. We use these results to distinguish causes of error generally from those on the ratio bias specifically and discuss the implications for our understanding of when the ratio bias occurs. Copyright © 2018 John Wiley & Sons, Ltd.     

School-based,randomised controlled trial of an evidence-based condom promotion leaflet

A condom use promotion leaflet was designed for use with older teenagers in schools. The text targeted a series of cognitive and behavioural antecedents of condom use identified in the literature. Given previous evidence that motivational incentives can enhance the effectiveness of health promotion leaflets, the leaflet was presented in conjunction with a quiz and prize draw. Students were randomly assigned to either the intervention condition or a (no leaflet or incentive) control condition. Measures were taken immediately, pre-intervention and 4 weeks later from 404 students. The 20-min intervention successfully promoted six of the eight measured cognitions, namely (1) attitude towards using condoms with a new partner (2) attitude towards using condoms with a steady partner (3) normative beliefs in relation to preparatory actions (4) self-efficacy in relation to both preparatory actions and (5) condom use (6) intention to use condoms, as well as three measured preparatory actions, that is, purchasing condoms, carrying condoms and discussing condom use. The intervention did not increase condom use with steady or new partners but power to test intervention impact on condom use was curtailed.     

最优化与满意型决策风格孰优孰劣?

最优化决策者追求决策的最优解,满意型决策者寻求决策的满意解.已有研究以理性模型和有限理性模型为基础,提出了两类决策风格的概念并且从两类决策者的决策特征和心理指标这两个角度详细对比了两类决策风格的差异.就纯粹的经济学效益、主观的心理学意义和现实的决策选择这三方面而言,“两类决策风格孰优孰劣”是一个因人而异,因决策目标而异的问题.未来研究可以在清晰界定两类决策风格概念的基础上进一步完善测量工具,从而深入探讨两类决策风格的领域特异性、与正性情绪的关系及其心理悖论的根源.     

Hail the impossible: p-values, evidence, and likelihood

Significance testing based on p-values is standard in psychological research and teaching. Typically, research articles and textbooks present and use p as a measure of statistical evidence against the null hypothesis (the Fisherian interpretation), although using concepts and tools based on a completely different usage of p as a tool for controlling long-term decision errors (the Neyman-Pearson interpretation). There are four major problems with using p as a measure of evidence and these problems are often overlooked in the domain of psychology. First, p is uniformly distributed under the null hypothesis and can therefore never indicate evidence for the null. Second, p is conditioned solely on the null hypothesis and is therefore unsuited to quantify evidence, because evidence is always relative in the sense of being evidence for or against a hypothesis relative to another hypothesis. Third, p designates probability of obtaining evidence (given the null), rather than strength of evidence. Fourth, p depends on unobserved data and subjective intentions and therefore implies, given the evidential interpretation, that the evidential strength of observed data depends on things that did not happen and subjective intentions. In sum, using p in the Fisherian sense as a measure of statistical evidence is deeply problematic, both statistically and conceptually, while the Neyman-Pearson interpretation is not about evidence at all. In contrast, the likelihood ratio escapes the above problems and is recommended as a tool for psychologists to represent the statistical evidence conveyed by obtained data relative to two hypotheses.     

In Search of a Reconciliation Between Semiotics,Thermodynamics and Metasystem Transition Theory

The disciplines of cybernetics, semiotics and thermodynamics investigate evolutionary processes quite independently from each other. The aim of this paper is to draw the parallels and point out the possibility and necessity of a reconciliation between these disciplines. The concept of metasystem transition has been proposed by Turchin as a quantum of evolution from a cybernetic point of view. Semiotic processes are of prime importance for the realisation of metasystem transitions in the course of evolution. From a thermodynamic point of view, the emergence of more complex, self-producing agents depends on the emergence of more advanced forms of semiosis. As an evolutionary consequence, more symbolic forms of semiosis that allow higher competence for abstraction and anticipation emerge.     

Analysis of Variance Models with Stochastic Group Weights

The analysis of variance (ANOVA) is still one of the most widely used statistical methods in the social sciences. This article is about stochastic group weights in ANOVA models – a neglected aspect in the literature. Stochastic group weights are present whenever the experimenter does not determine the exact group sizes before conducting the experiment. We show that classic ANOVA tests based on estimated marginal means can have an inflated type I error rate when stochastic group weights are not taken into account, even in randomized experiments. We propose two new ways to incorporate stochastic group weights in the tests of average effects – one based on the general linear model and one based on multigroup structural equation models (SEMs). We show in simulation studies that our methods have nominal type I error rates in experiments with stochastic group weights while classic approaches show an inflated type I error rate. The SEM approach can additionally deal with heteroscedastic residual variances and latent variables. An easy-to-use software package with graphical user interface is provided.     

Maximum Entropy Inference with Quantified Knowledge

We investigate uncertain reasoning with quantified sentencesof the predicate calculus treated as the limiting case of maximumentropy inference applied to finite domains.     

On Association Coefficients for 2×2 Tables and Properties That Do Not Depend on the Marginal Distributions

We discuss properties that association coefficients may have in general, e.g., zero value under statistical independence, and we examine coefficients for 2×2 tables with respect to these properties. Furthermore, we study a family of coefficients that are linear transformations of the observed proportion of agreement given the marginal probabilities. This family includes the phi coefficient and Cohen’s kappa. The main result is that the linear transformations that set the value under independence at zero and the maximum value at unity, transform all coefficients in this family into the same underlying coefficient. This coefficient happens to be Loevinger’s H.