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  2. Rubin causal model - Wikipedia

    en.wikipedia.org/wiki/Rubin_causal_model

    Rubin defines a causal effect: Intuitively, the causal effect of one treatment, E, over another, C, for a particular unit and an interval of time from to is the difference between what would have happened at time if the unit had been exposed to E initiated at and what would have happened at if the unit had been exposed to C initiated at : 'If an hour ago I had taken two aspirins instead of ...

  3. Spillover (experiment) - Wikipedia

    en.wikipedia.org/wiki/Spillover_(experiment)

    This assumption has also been called the Individualistic Treatment Response [8] or the stable unit treatment value assumption. Non-interference is violated when subjects can communicate with each other about their treatments, decisions, or experiences, thereby influencing each other's potential outcomes.

  4. Average treatment effect - Wikipedia

    en.wikipedia.org/wiki/Average_treatment_effect

    ATE requires a strong assumption known as the stable unit treatment value assumption (SUTVA) which requires the value of the potential outcome () be unaffected by the mechanism used to assign the treatment and the treatment exposure of all other individuals.

  5. Local average treatment effect - Wikipedia

    en.wikipedia.org/wiki/Local_average_treatment_effect

    The non-interference assumption, otherwise known as the Stable Unit Treatment Value Assumption (SUTVA), is composed of two parts. [ 12 ] The first part of this assumption stipulates that the actual treatment status, d i {\displaystyle d_{i}} , of subject i {\displaystyle i} depends only on the subject's own treatment assignment status, z i ...

  6. Field experiment - Wikipedia

    en.wikipedia.org/wiki/Field_experiment

    The non-interference assumption, or Stable Unit Treatment Value Assumption (SUTVA), indicates that the value of the outcome depends only on whether or not the subject is assigned the treatment and not whether or not other subjects are assigned to the treatment. When these three core assumptions are met, researchers are more likely to provide ...

  7. Difference in differences - Wikipedia

    en.wikipedia.org/wiki/Difference_in_differences

    Difference in differences (DID [1] or DD [2]) is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. [3]

  8. MetLife's Second Stable Value Study Finds Most Plan ... - AOL

    www.aol.com/news/2013-03-14-metlifes-second...

    When accessing stable value, nearly two-thirds of plan sponsors (62%) indicate that they predominantly access or arrange their stable value offerings through a recordkeeper or full-service ...

  9. Instrumental variables estimation - Wikipedia

    en.wikipedia.org/wiki/Instrumental_variables...

    For these reasons, IV methods invoke implicit assumptions on behavioral response, or more generally assumptions over the correlation between the response to treatment and propensity to receive treatment. [18] The standard IV estimator can recover local average treatment effects (LATE) rather than average treatment effects (ATE). [1]