Dealing with omitted answers in a survey on social integration of immigrants in Italy

ABSTRACT

Surveys are used to infer the level of social integration of immigrants. Item response theory helps to describe the relationship among responses to test items and latent traits of interest. However, in the presence of nonignorable missing data, which are omitted responses depending on the latent traits to be measured, estimates of the model parameters are biased. To account for nonignorable missing data, the quantity and quality of contacts between immigrants and natives (so called “social integration”) are taken into account through a linear function of the response propensity. Higher education, no intention to migrate again, young age, Albanian nationality, and declaring a non-Muslim religion or none, comparatively favor social integration.

KEYWORDS:

• Nonignorable missing data
• social integration
• item response theory
• latent regression model
• partial credit model