Impact of informativeness of the sample design on statistical inference

To determine and measure the impact of informativeness we compare design-based and model-based variances of estimated parameters, as well as the estimated parameters themselves, in a logistic model under the assumption that the postulated model is true. An approach for assessing the impact of informativeness is given. In order to address the additional complexity of the impact of informativeness on power, we propose a new approximation for a linear combination of non-central chi-square distributions, using generalized design effects. A large simulation study, based on generating a population under the postulated model, using parameter estimates derived from the NPHS, allows us to detect and to measure the informativeness, and to compare the robustness of studied approaches.