Modeling binary panel data with nonresponse
Modeling binary panel data with nonresponse
Abstract: This paper studies modeling of nonignorable nonresponse in panel surveys. A class of sequential conditional logistic models for nonresponse is considered. Model-based maximum likelihood estimation and imputation are used for estimating population proportions. Various models are evaluated, and comparisons are made with traditional methods of weighting and direct data imputation. Two cases are considered, (i) the population rate of participation in the 1989 Norwegian Storting election and (ii) estimation of car ownership in Norway in 1989 and 1990. Keywords: Nonignorable nonresponse, logistic modeling, imputation, election survey, consumer expenditure survey
- Statistics Norway Norway
JEL classification: C13, Logistic modeling, VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412, ddc:330, imputation, consumer expenditure survey, Consumer expenditure survey, Nonignorable nonresponse, election survey, C13, Election survey, C42, Nonignorable nonresponse; logistic modeling; imputation; election survey; consumer expenditure survey, logistic modeling, JEL classification: C42, jel: jel:C42, jel: jel:C13
JEL classification: C13, Logistic modeling, VDP::Mathematics and natural science: 400::Mathematics: 410::Statistics: 412, ddc:330, imputation, consumer expenditure survey, Consumer expenditure survey, Nonignorable nonresponse, election survey, C13, Election survey, C42, Nonignorable nonresponse; logistic modeling; imputation; election survey; consumer expenditure survey, logistic modeling, JEL classification: C42, jel: jel:C42, jel: jel:C13
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