The role of parametric assumptions in adaptive Bayesian estimation.


Autoria(s): Alcalá Quintana, Rocío; García Pérez, Miguel Ángel
Data(s)

01/06/2004

Resumo

Variants of adaptive Bayesian procedures for estimating the 5% point on a psychometric function were studied by simulation. Bias and standard error were the criteria to evaluate performance. The results indicated a superiority of (a) uniform priors, (b) model likelihood functions that are odd symmetric about threshold and that have parameter values larger than their counterparts in the psychometric function, (c) stimulus placement at the prior mean, and (d) estimates defined as the posterior mean. Unbiasedness arises in only 10 trials, and 20 trials ensure constant standard errors. The standard error of the estimates equals 0.617 times the inverse of the square root of the number of trials. Other variants yielded bias and larger standard errors.

Formato

application/pdf

Identificador

http://eprints.ucm.es/35705/1/alcal%C3%A1-quintana%20role%20of%20parametric%20assumptions.pdf.pdf

Idioma(s)

en

Relação

http://eprints.ucm.es/35705/

http://dx.doi.org/10.1037/1082-989X.9.2.250

doi.10.1037/1082-989X.9.2.250

AP2001-0759

BSO2001-1685

Direitos

info:eu-repo/semantics/restrictedAccess

Palavras-Chave #Psicología experimental #Psicometría
Tipo

info:eu-repo/semantics/article

PeerReviewed