When does information about causal structure improve statistical reasoning?

Base rate neglect on the mammography problem can be overcome by explicitly presenting a causal basis for the typically vague false-positive statistic. One account of this causal facilitation effect is that people make probabilistic judgements over intuitive causal models parameterized with the evidence in the problem. Poorly defined or difficult-to-map evidence interferes with this process, leading to errors in statistical reasoning. To assess whether the construction of parameterized causal representations is an intuitive or deliberative process, in Experiment 1 we combined a secondary load paradigm with manipulations of the presence or absence of an alternative cause in typical statistical reasoning problems. We found limited effects of a secondary load, no evidence that information about an alternative cause improves statistical reasoning, but some evidence that it reduces base rate neglect errors. In Experiments 2 and 3 where we did not impose a load, we observed causal facilitation effects. The amount of Bayesian responding in the causal conditions was impervious to the presence of a load (Experiment 1) and to the precise statistical information that was presented (Experiment 3). However, we found less Bayesian responding in the causal condition than previously reported. We conclude with a discussion of the implications of our findings and the suggestion that there may be population effects in the accuracy of statistical reasoning.

Whose statistical reasoning is improved by information about causal structure?

People often struggle when making Bayesian probabilistic estimates on the basis of competing sources of statistical evidence. Recently, Krynski and Tenenbaum (Journal of Experimental Psychology: General, 136, 430–450, 2007) proposed that a causal Bayesian framework accounts for peoples’ errors in Bayesian reasoning and showed that, by clarifying the causal relations among the pieces of evidence, judgments on a classic statistical reasoning problem could be significantly improved. We aimed to understand whose statistical reasoning is facilitated by the causal structure intervention. In Experiment 1, although we observed causal facilitation effects overall, the effect was confined to participants high in numeracy. We did not find an overall facilitation effect in Experiment 2 but did replicate the earlier interaction between numerical ability and the presence or absence of causal content. This effect held when we controlled for general cognitive ability and thinking disposition. Our results suggest that clarifying causal structure facilitates Bayesian judgments, but only for participants with sufficient understanding of basic concepts in probability and statistics.

Causal knowledge and the development of inductive reasoning

We explored the development of sensitivity to causal relations in children’s inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey → predator) or diagnostic (predator → prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children’s inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning.

Temporal and statistical information in causal structure learning

Three experiments examined children’s and adults’ abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a three-variable mechanical system that operated probabilistically. Participants of all ages preferentially relied on the temporal pattern of events in their inferences, even if this conflicted with statistical information. In Experiments 2 and 3, participants observed a series of interventions on the system, which in these experiments operated deterministically. In Experiment 2, participants found it easier to use temporal pattern information than statistical information provided as a result of interventions. In Experiment 3, in which no temporal pattern information was provided, children from 6-7 years, but not younger children, were able to use intervention information to make causal chain judgments, although they had difficulty when the structure was a common cause. The findings suggest that participants, and children in particular, may find it more difficult to use statistical information than temporal pattern information because of its demands on information processing resources. However, there may also be an inherent preference for temporal information.

Genetic Evidence for a Causal Role of Obesity in Diabetic Kidney Disease

Obesity has been posited as an independent risk factor for diabetic kidney disease (DKD), but establishing causality from observational data is problematic. We aimed to test whether obesity is causally related to DKD using Mendelian randomization, which exploits the random assortment of genes during meiosis. In 6,049 subjects with type 1 diabetes, we used a weighted genetic risk score (GRS) comprised of 32 validated BMI loci as an instrument to test the relationship of BMI with macroalbuminuria, end-stage renal disease (ESRD), or DKD defined as presence of macroalbuminuria or ESRD. We compared these results with cross-sectional and longitudinal observational associations. Longitudinal analysis demonstrated a U-shaped relationship of BMI with development of macroalbuminuria, ESRD, or DKD over time. Cross-sectional observational analysis showed no association with overall DKD, higher odds of macroalbuminuria (for every 1 kg/m(2) higher BMI, odds ratio [OR] 1.05, 95% CI 1.03-1.07, P < 0.001), and lower odds of ESRD (OR 0.95, 95% CI 0.93-0.97, P < 0.001). Mendelian randomization analysis showed a 1 kg/m(2) higher BMI conferring an increased risk in macroalbuminuria (OR 1.28, 95% CI 1.11-1.45, P = 0.001), ESRD (OR 1.43, 95% CI 1.20-1.72, P < 0.001), and DKD (OR 1.33, 95% CI 1.17-1.51, P < 0.001). Our results provide genetic evidence for a causal link between obesity and DKD in type 1 diabetes. As obesity prevalence rises, this finding predicts an increase in DKD prevalence unless intervention should occur.

Age- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors

Observational studies have reported different effects of adiposity on cardiovascular risk factors across age and sex. Since cardiovascular risk factors are enriched in obese individuals, it has not been easy to dissect the effects of adiposity from those of other risk factors. We used a Mendelian randomization approach, applying a set of 32 genetic markers to estimate the causal effect of adiposity on blood pressure, glycemic indices, circulating lipid levels, and markers of inflammation and liver disease in up to 67,553 individuals. All analyses were stratified by age (cutoff 55 years of age) and sex. The genetic score was associated with BMI in both nonstratified analysis (P = 2.8 × 10(-107)) and stratified analyses (all P < 3.3 × 10(-30)). We found evidence of a causal effect of adiposity on blood pressure, fasting levels of insulin, C-reactive protein, interleukin-6, HDL cholesterol, and triglycerides in a nonstratified analysis and in the <55-year stratum. Further, we found evidence of a smaller causal effect on total cholesterol (P for difference = 0.015) in the ≥55-year stratum than in the <55-year stratum, a finding that could be explained by biology, survival bias, or differential medication. In conclusion, this study extends previous knowledge of the effects of adiposity by providing sex- and age-specific causal estimates on cardiovascular risk factors.

Children's use of interventions to learn causal structure

Children aged between 5 and 8 years freely intervened on a three-variable causal system, with their task being to discover whether it was a common-cause structure or one of two causal chains. From 6-7 years, children were able to use information from their interventions to correctly disambiguate the structure of a causal chain. We used a Bayesian model to examine children’s interventions on the system; this showed that with development children became more efficient in producing the interventions needed to disambiguate the causal structure and that the quality of interventions, as measured by their informativeness, improved developmentally. The latter measure was a significant predictor of children’s correct inferences about the causal structure. A second experiment showed that levels of performance were not reduced in a task in which children did not select and carry out interventions themselves, indicating no advantage for self-directed learning. However, children’s performance was not related to intervention quality in these circumstances, suggesting that children learn in a different way when they carry out interventions themselves.

The Influence of Causal Explanations and Diagnostic Labeling on Psychology Students’ Beliefs About Treatments, Prognosis, Dangerousness and Unpredictability in Schizophrenia

This study explored views of 566 Italian psychology students about schizophrenia. The most frequently cited causes were psychological traumas (68%) and heredity (54%). Thirty-three percent of students firmly believed that people with the condition could recover. Reporting heredity among the causes, and identifying schizophrenia were both associated with prognostic pessimism, greater confidence in pharmacological treatments and lower confidence in psychological treatments. Schizophrenia labeling was also associated with higher perception of unpredictability and dangerousness. Compared to first year students, fourth/fifth year students more frequently reported heredity among the causes, and were more pessimistic about schizophrenia recovery. Stigma topics should be included in future psychologists’ education.

Interrelationship between two variants of the Circulifer tenellus complex and Spiroplasma citri: the causal agent of stubborn disease

Tese de Doutoramento, Ciências Naturais, Unidade de Ciências e Tecnologias Agrárias, Universidade do Algarve, 1992

The causal relationship between private and public investment in Zimbabwe

Aims: The study examines the relationship between private and public investment in Zimbabwe utilizing yearly time series data for the period 1967 to 2004. Study Design: Time Series Study. Place and Duration of Study: Zimbabwe, May 2011 to July 2011. Methodology: Emphasis is placed on the direction of causality and the long run and short run effect of the two types of investment on each other. The paper constructs empirical models for both private and public investment, based on the flexible accelerator theory. Private investment is found to be cointegrated with public investment. A cointergration and VEC models are employed to assess the long and short run relationship existing between public and private investment. Conclusion: The relationship between private and public investment is found to be insignificant and the direction of causality found to be unidirectional. The results support the notion that private investment precedes public investment.

Investigating the causal role of rightOFA in holistic detection of Mooney faces and objects: an fMRI-guided TMS study

Background The right occipital face area (rOFA) is known to be involved in face discrimination based on local featural information. Whether this region is involved in global, holistic stimulus processing is not known. Objective We used fMRI-guided transcranial magnetic stimulation (TMS) to investigate whether rOFA is causally implicated in stimulus detection based on holistic processing, by the use of Mooney stimuli. Methods Two studies were carried out: In Experiment 1, participants performed a detection task involving Mooney faces and Mooney objects; Mooney stimuli lack distinguishable local features and can be detected solely via holistic processing (i.e. at a global level) with top-down guidance from previously stored representations. Experiment 2 required participants to detect shapes which are recognized via bottom-up integration of local (collinear) Gabor elements and was performed to control for specificity of rightOFA's implication in holistic detection. Results In Experiment 1, TMS over rOFA and rLO impaired detection of all stimulus categories, with no category-specific effect. In Experiment 2, shape detection was impaired when TMS was applied over rLO but not over rOFA. Conclusions Our results demonstrate that rOFA is causally implicated in the type of top-down holistic detection required by Mooney stimuli and that such role is not face-selective. In contrast, rOFA does not appear to play a causal role in in detection of shapes based on bottom-up integration of local components, demonstrating that its involvement in processing non-face stimuli is specific for holistic processing.

exploring the differences of CSR and CSE activities on consumer attributions and responses

The following directed research project analyzes how different sustainability efforts of an organization influence consumers’ responses in an industry, which faces high controversy. The study tested shows how two different high fit sustainability endeavors, namely high fit Corporate Social Responsibility (CSR) activities and Corporate Social Entrepreneurship (CSE), affect the way consumers’ attributions are being made with regard to the company’s motive. With data gathered from surveying 156 participants, the study provides evidence that CSR as well as CSE programs stimulate values-driven attributions which positively affect consumers’ trust, corporate reputation and corporate image. Lastly, theoretical and managerial implications of the study are discussed and future research suggestions provided.

Counterfactuals and causal inference: Methods and principles for social research

"Most quantitative empirical analyses are motivated by the desire to estimate the causal effect of an independent variable on a dependent variable. Although the randomized experiment is the most powerful design for this task, in most social science research done outside of psychology, experimental designs are infeasible. (Winship & Morgan, 1999, p. 659)." This quote from earlier work by Winship and Morgan, which was instrumental in setting the groundwork for their book, captures the essence of our review of Morgan and Winship's book: It is about causality in nonexperimental settings.