Huber, Martin 2012 As any empirical method used for causal analysis, social experiments are prone to attrition which may flaw the validity of the results. This paper considers the problem of partially missing outcomes in experiments. Firstly, it systematically reveals under which forms of attrition - in terms of its relation to observable and/or unobservable factors - experiments do (not) yield causal parameters. Secondly, it shows how the various forms of attrition can be controlled for by different methods of inverse probability weighting (IPW) that are tailored to the specifi c missing data problem at hand. In particular, it discusses IPW methods that incorporate instrumental variables when attrition is related to unobservables, which has been widely ignored in the experimental literature before. application/pdf https://folia.unifr.ch/global/documents/309358 https://folia.unifr.ch/documents/309358/files/2012_Huber_Identification.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.3102/1076998611411917 info:eu-repo/semantics/openAccess License undefined Journal of Educational and Behavioral Statistics. - SAGE Publications. - 2012, vol. 37, no. 3, p. 443-474 experiments attrition inverse probability weighting info:eu-repo/classification/udc/33 Identification of Average Treatment Effects in Social Experiments Under Alternative Forms of Attrition http://purl.org/coar/resource_type/c_6501