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Vine Copulas for Imputation of Monotone Non‐response
Author(s) -
Hasler Caren,
Craiu Radu V.,
Rivest LouisPaul
Publication year - 2018
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/insr.12263
Subject(s) - vine copula , bivariate analysis , mathematics , joint probability distribution , copula (linguistics) , imputation (statistics) , missing data , econometrics , statistics , conditional probability distribution , marginal distribution , random variable
Summary Monotone patterns of non‐response may occur in longitudinal studies. When the measured variables are dependent, it is beneficial to use their joint statistical model to impute the missing values. We propose to use vine copulas to factorise the density of the observed variables into a cascade of bivariate copulas that yield a flexible model of their joint distribution. The structure of the vine depends on the non‐response pattern. We propose a method to select the model, to estimate the parameters of the bivariate copulas of the selected model and to impute using the constructed model. The imputed values are drawn from the conditional distribution of the missing values, given the observed data. We discuss the generalisation of our results to more global non‐response patterns.