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Abstract: Concerns about decreasing response rates have led to many nonresponse studies. Unfortunately, usually only a limited amount of data is available on nonrespondents. Linking administrative data makes information available on all the sampled units including nonrespondents. Statistics Netherlands has constructed a database in which several administrative records and several surveys are connected. In this explorative study we use this dataset to look for homogenous groups of respondents and nonrespondents in survey research using latent class cluster analysis. Latent class techniques can provide insight into the problem of selective nonresponse and currently under-represented societal groups. We identify four different latent classes in a recent Dutch survey and replicate the findings for the same survey conducted 4 years later. Two of the types of sampled units have above-average response rates and the other two have below-average response rates. We also evaluate various latent class models with other response outcomes to gain insight into the contact and cooperation process. [Copyright &y& Elsevier]