Discussion Papers no. 274

Markov chain generated profile likelihood inference under generalized proportional to size non-ignorable non-response

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Åpne og les publikasjonen i PDF (18 sider)

We apply two non-ignorable non-response models to the data of the Norwegian Labour Force Survey, the Fertility Survey and the Alveolar Bone Loss Survey. Both models focus on the marginal effect which the object variable of interest has on the non-response, where we assume the probability of non-response to be generalized proportional to the size of the object variable. We draw the inference of the parameter of interest based on the first-order theory of the profile likelihood. We adapt the Markov chain sampling techniques to efficiently generate the profile likelihood inference. We explain and demonstrate why the resampling approach is more flexible for the likelihood inference than under the Beyesian framework.

Om publikasjonen

Tittel

Markov chain generated profile likelihood inference under generalized proportional to size non-ignorable non-response

Ansvarlige

Ib Thomsen, Joseph Sexton, Li-Chun Zhang

Serie og -nummer

Discussion Papers no. 274

Utgiver

Statistics Norway, Research Department

Emne

Discussion Papers

Antall sider

18

Målform

Engelsk

Om Discussion Papers

Discussion papers comprise research papers intended for international journals and books. A preprint of a Discussion Paper may be longer and more elaborate than a standard journal article as it may include intermediate calculations, background material etc.

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