The debate on free will is dominated by the discussion between compatibilists and incompatibilists. The central intuition of the incompatibilist is that the future must be open; on the other hand,... Show moreThe debate on free will is dominated by the discussion between compatibilists and incompatibilists. The central intuition of the incompatibilist is that the future must be open; on the other hand, for the compatibilist it makes no difference to free will whether or not the laws of nature are deterministic. This paper argues that we can hold the incompatiblist and compatibilist intuitions together with the doctrine of free will, on the condition that we deny the seemingly evident claim that determinism implies a closed future. In order to deny this claim, I develop a new version of presentism that I call causal presentism. The causal presentist holds that only the present exists, and that statements about the past and the future are statements about what the present causally implies. Within this framework, the open future and determinism are compatible so long as we are willing to accept that our present choices determine not just the future, but also the past. I discuss several counterarguments that can be brought against this idea, showing that they lack force. In doing so, I demonstrate that causal presentism is worthy of further development. Show less
Ramspek, C.L.; Steyerberg, E.W.; Riley, R.D.; Rosendaal, F.R.; Dekkers, O.M.; Dekker, F.W.; Diepen, M. van 2021
Etiological research aims to uncover causal effects, whilst prediction research aims to forecast an outcome with the best accuracy. Causal and prediction research usually require different methods,... Show moreEtiological research aims to uncover causal effects, whilst prediction research aims to forecast an outcome with the best accuracy. Causal and prediction research usually require different methods, and yet their findings may get conflated when reported and interpreted. The aim of the current study is to quantify the frequency of conflation between etiological and prediction research, to discuss common underlying mistakes and provide recommendations on how to avoid these. Observational cohort studies published in January 2018 in the top-ranked journals of six distinct medical fields (Cardiology, Clinical Epidemiology, Clinical Neurology, General and Internal Medicine, Nephrology and Surgery) were included for the current scoping review. Data on conflation was extracted through signaling questions. In total, 180 studies were included. Overall, 26% (n = 46) contained conflation between etiology and prediction. The frequency of conflation varied across medical field and journal impact factor. From the causal studies 22% was conflated, mainly due to the selection of covariates based on their ability to predict without taking the causal structure into account. Within prediction studies 38% was conflated, the most frequent reason was a causal interpretation of covariates included in a prediction model. Conflation of etiology and prediction is a common methodological error in observational medical research and more frequent in prediction studies. As this may lead to biased estimations and erroneous conclusions, researchers must be careful when designing, interpreting and disseminating their research to ensure this conflation is avoided. Show less
