Summary: 29 instances, 22 unique

Text	Count
# TODO we are conditioning on a postive treatment	1
# TODO remove neighbors that are more than a given radius apart	2
# TODO - how can we add additional information into the returned estimate?	2
#TODO add propensity score as default backdoor method, iv as default iv method, add an informational message to show which method has been selected.	1
# TODO create an expression corresponding to each estimator used	1
# TODO Refactor to remove this from here and only implement this logic in causalIdentifier. Unnecessary assumption of nodes1 to be causing nodes2.	1
# TODO: outputs string for now, but ideally should do symbolic	1
TODO: Needs an interpretation module	1
# TODO -- fix: we are actually conditioning on positive treatment (d=1)	4
#self._graph.add_edge(outcome, node_name, style = "dotted", headport="n", tailport="s") # TODO make the ports more general so that they apply not just to top-bottom node configurations	1
# TODO: A common way to show all plots	1
# [TODO: double check these work with multivariate implementation:]	1
# TODO Ensure that we do not generate weak instruments	1
# TODO Better support for multivariate treatments	1
# TODO: support multivariate treatments better.	3
# TODO: This add_params needs to move to the estimator class	1
# TODO Only works for binary treatment	1
# TODO add dowhy as a prefix to all dowhy estimators	1
# TODO move this to the identification step	1
# TODO: Looking for contributions	1
# TODO - test all our methods with random noise added to covariates (instead of the stochastic treatment assignment)	1
# TODO make treatment_value and control value also as local parameters	1