The British Journal for the Philosophy of Science · 2017 · 60 citations · 25 references
Public HealthBiostatisticsCausal InferenceExperimental DesignMeta-analysisBiasBias ControlCausal Effect EstimationRandomized Comparative TrialsRandomized Controlled TrialsBias In Randomized TrialsComparison Group DesignConfoundingConfounding AdjustmentConfounding BiasConfounding ControlRandomizationRandomized Experiments
It is sometimes thought that randomized study group allocation is uniquely proficient at producing comparison groups that are evenly balanced for all confounding causes. Philosophers have argued that in real randomized controlled trials this balance assumption typically fails. But is the balance assumption an important ideal? I run a thought experiment, the CONFOUND study, to answer this question. I then suggest a new account of causal inference in ideal and real comparative group studies that helps clarify the roles of confounding variables and randomization. 1Confounders and Causes2The Balance Assumption3The CONFOUND Study 3.1CONFOUND 13.2CONFOUND 24Disjunction C and the Ideal Study 4.1The ultimate 'other cause': C4.2The ideal comparative group study4.3Required conditions for causal inference5Confounders as Causes, Confounders as Correlates6Summary.
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