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Is causal induction based on causal power? Critique of Cheng (1997).

The authors empirically evaluate P. W. Cheng's (1997) power PC theory of causal induction. They reanalyze some published data taken to support the theory and show instead that the data are at variance with it. Then, they report 6 experiments in which participants evaluated the causal relationship between a fictitious chemical and DNA mutations. The power PC theory assumes that participants' estimates are based on the causal power p of a potential cause, where p is the contingency between the cause and the effect normalized by the base rate of the effect. Three of the experiments used a procedure in which causal information was presented trial by trial. For these experiments, the power PC theory was contrasted with the predictions of the probabilistic contrast model and the Rescorla-Wagner theory. For the remaining 3 experiments, a summary presentation format was employed to which only the probabilistic contrast model and the power PC theory are applicable. The power PC theory was unequivocally contradicted by the results obtained in these experiments, whereas the other 2 theories proved to be satisfactory.

Adult↗

Causality assessment of adverse reactions to drugs--II. An original model for validation of drug causality assessment methods: case reports with positive rechallenge.

Standards are lacking for validation of drug causality assessment methods. An original model is proposed using a positive rechallenge as an external standard. This model was used to validate the novel causality assessment method (RUCAM) described in the previous article (Part I; J Clin Epidemiol 1993; 46: 1323). Seventy seven reports of drug-induced acute liver injuries with positive rechallenge were collected from the medical literature and divided into 49 cases and 28 controls. The RUCAM was applied to information obtained prior to readministration. The score was significantly higher (p < 10(-4)) in cases than in controls with high levels of sensitivity, specificity and predictive values. It is concluded that (1) adverse drug reaction reports with a positive rechallenge can provide a standard for validation of causality assessment methods, (2) RUCAM applied to drug-induced liver injuries has been validated.

Age Factors↗

The causal relationship between socioeconomic factors and alcohol consumption: a Granger-causality time series analysis, 1950-1993.

OBJECTIVE: This article examines the relationships between social, demographic and economic factors that influence alcohol consumption. METHOD: The effects of each factor on alcohol consumption and on each other is examined using a Granger-causality time series framework. Specifically, causal determinations are made between per capita alcohol consumption, social and demographic variables consisting of the age structure of the male population, female labor force participation rates, marital instability and educational accomplishment, and the economic variables consisting of the real price of alcohol, median household income and income inequality. Causal equations are determined from identified bivariate relationships and combined into one structural equation predicting alcohol consumption. RESULTS: The findings indicate that the economic variables are Granger-caused by the social or demographic changes over the past four decades and, therefore, have little direct influence on alcohol consumption. The structural equation predicts over 95% of the variance in alcohol consumption. CONCLUSIONS: This work indicates that economic factors have little direct influence on alcohol consumption but, rather, reflect or are a conduit for changes in social and demographic variables. Excluding economic variables as predictors of per capita ethanol consumption results in little substantive change when estimating alcohol consumption.

Age Factors↗

[To the problems of causality in medicine: the case of viruses and tumors--I. General principles of causal studies in medicine].

Clarification of the aetiology of chronic human diseases such as atherosclerosis or cancer is one of the dominant topics in the contemporary medical research. It is believed that identification of the causal factors will enable more efficient prevention and diagnosis of these diseases and, in some instances, also permit more effective therapy. The task is difficult because of the multistep and multifactorial origin of these diseases. In this paper the author attempts to review the present methodological approaches to aetiological studies of chronic diseases and discusses the role of criteria for identifying causal relationships.

Causality↗

Constructing causal scenarios: a knowledge structure approach to causal reasoning.

A model of causal reasoning based on Schank and Abelson's (1977) analysis of knowledge structures is presented. The first part of this article outlines the necessary characteristics of such a model. It is argued that a central attributional problem is to explain extended sequences of behavior. To do this people must relate actions in a sequence to one another and construct a coherent scenario from them. Because the relation among actions is not given, people must use detailed social and physical knowledge to make connecting inferences. The resulting scenario typically includes information about the plans and goals of the actor. The second part of this article analyzes how the knowledge structures outlined by Schank and Abelson (1977)--scripts, plans, goals, and themes--can be used to construct such causal scenarios, and it presents a process model for the construction of such scenarios. The last part of this article examines the implications of this model and its relations to other attribution models by Kelley (1967, 1971a, 1971b) and Jones (Jones & Davis, 1965; Jones & McGillis, 1976).

Cognition↗

Causal judgement from contingency information: judging interactions between two causal candidates.

In two experiments participants judged the extent to which occurrences and non-occurrences of an effect could be attributed to an interaction between two causal candidates A and B. In Experiment I judgements were influenced by the proportion of instances normatively evaluated as confirmatory for the interaction interpretation, when the objective contingency was held constant. Information about instances in which both candidates were present and the effect occurred was more influential than information about instances in which both candidates were absent and the effect did not occur. In Experiment 2 the occurrence rate of the effect when both candidates were present, when A alone was present, when B alone was present, and when both were absent was manipulated. Interaction judgements were mainly determined by occurrence rate when both were present. There was also a significant effect of occurrence rate when both were absent, but the other two occurrence rates had no significant effect. These results are interpreted as supporting a general model in which causal judgements are made according to the proportion of instances evaluated as supporting the interpretation being judged.

Adult↗

Constructing a causal model of African human trypanosomiasis. The Antwerp Trypanosomiasis Causal Modelling Group.

Following the TDR/WHO sponsored Workshop on Modelling Sleeping Sickness Epidemiology and Control, 25-29 January 1988, Antwerp, a group of scientists at the Institute of Tropical Medicine "Prince Leopold" (ITM), Antwerp, started to develop a causal model of human african trypanosomiasis. The group hypothesised a series of relations between determinants and associated factors of the prevalence of sleeping sickness. These relations were pictured in a logically structured hierarchial representation of the causal web of sleeping sickness.

Animals↗

[Implicit causality in language: criteria for selection of stimulus material in studies of verb causality].

Studies dealing with the implicit causality in verbs have shown that even minimal descriptions of interpersonal events (e.g. "Michael apologizes to Peter" or "Vera admires Karen") systematically elicit attributions toward the sentence subject or sentence object. However, in the majority of existing studies, the stimulus materials (i.e., interpersonal verbs) have not been selected randomly: Verbs were selected either because they had often been used in previous studies, or they were counterbalanced with regard to a number of additional criteria (valence, derivational form, etc.), and therefore, a truly random sampling of stimulus verbs were impossible. In the present study, the criteria for selecting interpersonal verbs are varied in order to compare two groups of verbs, namely, verbs which have been used very often in previous studies versus a random sample of interpersonal verbs. It is shown that the classical findings concerning the perceived causes of interpersonal verbs are less pronounced for the random sample than for the non-random sample of interpersonal verbs. However, even for the random sample of verbs, an impressive amount of variance in causal attributions is explained by different verb types.

Adult↗

God does not play dice: causal determinism and preschoolers' causal inferences.

Three studies investigated children's belief in causal determinism. If children are determinists, they should infer unobserved causes whenever observed causes appear to act stochastically. In Experiment 1, 4-year-olds saw a stochastic generative cause and inferred the existence of an unobserved inhibitory cause. Children traded off inferences about the presence of unobserved inhibitory causes and the absence of unobserved generative causes. In Experiment 2, 4-year-olds used the pattern of indeterminacy to decide whether unobserved variables were generative or inhibitory. Experiment 3 suggested that children (4 years old) resist believing that direct causes can act stochastically, although they accept that events can be stochastically associated. Children's deterministic assumptions seem to support inferences not obtainable from other cues.

Biological Evolution↗