Sensitivity Analysis Without Assumptions

eAppendix for “Sensitivity Analysis Without Assumptions”

Sensitivity analysis: distributional assumptions and confounding assumptions.

In a presentation of various methods for assessing the sensitivity of regression results to unmeasured confounding, Lin, Psaty, and Kronmal (1998, Biometrics54, 948-963) use a conditional independence assumption to derive algebraic relationships between the true exposure effect and the apparent exposure effect in a reduced model that does not control for the unmeasured confounding variable. How...

Sensitivity analysis and distributional assumptions

In a presentation of various methods for assessing the sensitivity of regression results to unmeasured confounding, Lin et al. (1998) use a conditional independence assumption to derive algebraic relationships between the true exposure e¤ect and the apparent exposure e¤ect in a reduced model which does not control for the unmeasured confounding variable. However, Hernán and Robins (1999) have n...

Measuring Productivity Change without Neoclassical Assumptions: A Conceptual Analysis

The measurement of productivity change (or difference) is usually based on models that make use of strong assumptions such as competitive behaviour and constant returns to scale. This survey discusses the basics of productivity measurement and shows that one can dispense with most if not all the usual, neoclassical assumptions. By virtue of its structural features, the measurement model is appl...

Group Signatures Without q-Assumptions

The notion of group signatures was introduced to allow group members to sign anonymously on behalf of a group. A group manager allows a user to join a group, and another will be able to open a signature to revoke its anonymity. Several schemes have already been proposed to fulfil these properties, however very few of them are proven in the standard model. Of those proven in the standard model, ...