We provide evidence from a large-scale field experiment on the causal effects of audit rules on compliance in a market for long-term care. In this setting care should be provided quickly and, therefore, the gatekeeper introduced ex-post auditing. Our results do not show significant effects of variations in random audit rates and switching to a conditional audit regime on the quantity and qualit...

cplint is a suite of programs for reasoning and learning with Probabilistic Logic Programming languages that follow the distribution semantics. In this paper we describe how we have extended cplint to perform causal reasoning. In particular, we consider Pearl’s do calculus for models where all the variables are measured. The two cplint modules for inference, PITA and MCINTYRE, have been extende...

Abstract Directionality in coupling, defined as the linkage relating causes to their effects at a later time, can be used to explain the core dynamics of ecological systems by untangling direct and feedback relationships between the different components of the systems. Inferring causality from measured ecological variables sampled through time remains a formidable challenge further made diffic...

We suggest and test an integrated framework explaining how the interpretation of and the reasoning from causal conditionals (e.g., "If you fertilize a flower it will bloom") depend on exceptions. In the model availability of exceptional situations (e.g., "the flower was not watered enough") reduces the subjective conditional probability of the consequent given the antecedent, P(q p). The condit...

The discovery of causal relationships from empirical data is an important problem in machine learning. In this paper the attention is focused on the inference o fprobabilis tic causal relationships, for which two different approaches, namely Glymour et al.'s approach based on constraints on correlations and Pearl and Verma's approach based on conditional independencies, have been proposed. Thes...

Three kinds of independence are of interest in the context of Bayesian networks, namely conditional independence, independence of causal in uence, and context-speci c independence. It is well-known that conditional independence enables one to factorize a joint probability into a list of conditional probabilities and thereby renders inference feasible. It has recently been shown that independenc...

IV Computational Mechanics 9 A Causal States . . . . . . . . . . . . . . 9 Causal States of a Process Defined . . . 9 1 Morphs . . . . . . . . . . . . . . . . 10 Independence of Past and Future Conditional on a Causal State . . . 10 2 Homogeneity . . . . . . . . . . . . . 11 Strict Homogeneity . . . . . . . . . 11 Weak Homogeneity . . . . . . . . . 11 Strict Homogeneity of Causal States 11 B Ca...

In contrast to statistical methods, a number of case study methods—collectively referred to as Mill’s methods, used by generations of social science researchers—only consider deterministic relationships. They do so to their detriment because heeding the basic lessons of statistical inference can prevent serious inferential errors. Of particular importance is the use of conditional probabilities...

Acausal rule between two variables, X! Y , captures the relationship that the presence of X causes the appearance of Y. Because of its usefulness (compared to association rules), techniques for mining causal rules are beginning to be developed. However, the effectiveness of existing methods (such as the LCD and CU-path algorithms)are limited to mining causal rules among simple variables, and ar...

Yu-Fang Wang Graduate Institute of English , National Taiwan Normal University Abstract In conversation, adverbial clause subordination is most commonly achieved through temporal, conditional, concessive, and causal conjunctions, such as dang (` when'), ruguoCin, suiran (`although'), yinwei (` because'), etc. in Mandarin Chinese. This study aims at exploring adverbial clauses in spoken Mandarin...