### abstract ###
fiedler et al CITATION   reviewed evidence for the utilization of a contingency inference strategy termed pseudocontingencies pcs
in pcs  the more frequent levels and  by implication  the less frequent levels are assumed to be associated
pcs have been obtained using a wide range of task settings and dependent measures
yet  the readiness with which decision makers rely on pcs is poorly understood
a computer simulation explored two potential sources of subjective validity of pcs
first  pcs are shown to perform above chance level when the task is to infer the sign of moderate to strong population contingencies from a sample of observations
second  contingency inferences based on pcs and inferences based on cell frequencies are shown to partially agree across samples
intriguingly  this criterion and convergent validity are by-products of random sampling error  highlighting the inductive nature of contingency inferences
### introduction ###
accurate contingency assessment is a prerequisite to  explain the past  control the present and predict the future   CITATION
from an adaptive cognition perspective  assessing contingencies amounts to inferring the relationship between two variables in a population from a sample of observations drawn from that population  CITATION
if the task was to evaluate the relation between drinking one of two beverages  say red wine or beer  and developing a migraine or not  the contingency may be inferred from recalling instances of wine and beer consumption followed or not followed by a migraine
epistemologically  then  the contingency in a sample  or more precisely the specific contingency index used by the decision maker  is used as a proxy for the contingency in the general population of instances
for example  to the degree that for the last  NUMBER  instances of alcohol consumption the proportion of developing a migraine was higher after red wine than after beer  one might conclude that in general red wine is more conductive of migraine than beer
not only for the   x NUMBER  p index in this example but for most contingency indices this inference seems unproblematic  as the sign and size of the sample value are unbiased estimates of the population value  CITATION
what might be more problematic is the quality grade of the information required
virtually all traditional contingency indices require information about joint occurrences
in other words  for every instance in a sample it is necessary to know the levels of both variables
in the example  for every consumption instance one needs to be sure whether red wine or beer had been consumed and whether it was followed by a migraine or not
however  due to several factors  e g a delay between observing the variables or a large amount of variables to be considered  information about joint occurrences might not be available at the time of judgment  preventing the use of the common contingency indices
in the remainder  we will discuss the validity of an alternative strategy for contingency inferences that is applicable even under such impoverished conditions  pseudocontingencies
pcs denote using the skew greater numbers of one level than the other in the case of dichotomous variables in the sample base rates of a pair of variables to infer a contingency
it is obvious that by using base rates  pcs do not require information about joint occurrences
however  because base rates are largely independent from contingencies  it is less obvious why pcs should be used at all
while independence is true descriptively at the population level  we will show that random sampling error necessarily causes population contingencies to translate into skewed sample base rates
intriguingly  these sample base rates  skewed by the sampling process  enable pcs to successfully indicate moderate to strong population contingencies
as another consequence  strategies that  rely on joint occurrences mostly agree with the pcs' predictions across  samples
