Imputation algorithm using copulas

Povzetek

In this paper the author demonstrates how the copulas approach can be used to find algorithms for imputing dropouts in repeated measurements studies. One problem with repeated measurements is the knowledge that the data is describedby joint distribution. Copulas are used to create the joint distribution with given marginal distributions. Knowing the joint distributionwe can find the conditional distribution of the measurement at a specific time point, conditioned by past measurements, and this will be essential for imputing missing values. Using Gaussian copulas, two simple methods for imputation are presented. Compound symmetry and the case of autoregressive dependencies are discussed. Effectiveness of the proposed approach is tested via series of simulations and results showing that the imputation algorithms based on copulas are appropriate for modelling dropouts.

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Podatki

Jezik:	Angleški jezik
Leto izida:	2006
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	UL FDV - Fakulteta za družbene vede
Založnik:	Fakulteta za družbene vede
UDK:	303
COBISS:	25331293
ISSN:	1854-0023
Št. ogledov:	557
Št. prenosov:	39
Ocena:	0 (0 glasov)
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Ostali podatki

Sekundarni jezik:	Neznan jezik
URN:	URN:NBN:SI
Vrsta dela (COBISS):	Delo ni kategorizirano
Strani:	str. 109-120
Letnik:	ǂVol. ǂ3
Zvezek:	ǂno. ǂ1
Čas izdaje:	2006
Ključne besede (UDK):	social sciences;družbene vede;methods of the social sciences;metode družbenih ved;
ID:	40638