izpis_h1_title_alt

Correcting measurement error bias in interaction models with small samples
Bisbe, Josep (Avtor), Coenders, Germà (Avtor), Saris, Willem E. (Avtor), Batista-Foguet, Joan Manuel (Avtor)

URLURL - Predstavitvena datoteka, za dostop obiščite http://mrvar.fdv.uni-lj.si/pub/mz/mz3.1/bispe.pdf Povezava se odpre v novem oknu

Izvleček
Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use ofbudgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made withthe alternative methods. Methods that do not correct for measurement errorbias perform very similarly and considerably worse than disattenuated regression.

Jezik:Angleški jezik
Vrsta gradiva:Delo ni kategorizirano (r6)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FDV - Fakulteta za družbene vede
Leto izida:2006
Št. strani:Str. 267-287
Številčenje:Vol. 3, no. 2
UDK:303
ISSN pri članku:1854-0023
COBISS.SI-ID:25333341 Povezava se odpre v novem oknu
Število ogledov:671
Število prenosov:165
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
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Naslov:Metodološki zvezki
Skrajšan naslov:Metodol. zv.
Založnik:Fakulteta za družbene vede
ISSN:1854-0023
COBISS.SI-ID:215795712 Povezava se odpre v novem oknu

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