Abstract:
In this study, the problem of nonrespondents in longitudinal survey’s data is considered.
The study focuses on the imputation for the longitudinal survey data which
often has nonignorable nonrespondents. Local linear regression is used to impute the
missing values of and then the estimation of the time-dependent finite populations
means. The estimation of the time dependent means was based on the assumption
that the nonresponse mechanism is last past value dependent. The asymptotic unbiasedness
and consistency of the proposed estimator are investigated. The imputation
for the nonmonotone nonrespondents is done multiple times through simulation and
the simulation study is carried out to asses the best performing estimator of the
time-dependent finite populations means. Comparisons between different parametric
and nonparametric estimators are performed based on the bootstrap standard
deviation, mean square error and percentage relative bias. The simulation results
show that local linear regression estimator yields good properties.
