Artigo
Bayesian approximations in randomized response model
Fecha
1997-06-05Registro en:
Computational Statistics & Data Analysis. Amsterdam: Elsevier B.V., v. 24, n. 4, p. 401-409, 1997.
0167-9473
10.1016/S0167-9473(96)00075-8
WOS:A1997XE92300003
2943659125242224
Autor
Universidade Federal do Rio de Janeiro (UFRJ)
Universidade Estadual Paulista (Unesp)
Resumen
Practical Bayesian inference depends upon detailed examination of posterior distribution. When the prior and likelihood are conjugate, this is easily carried out; however, in general, one must resort to numerical approximation. In this paper, our aim is to solve, using MAPLE, the Bayesian paradigm, for a very special data collecting procedure, known as the randomized-response technique. This allows researchers to obtain sensitive information while guaranteeing privacy to respondents. This approach intends to reduce false responses on sensitive questions. Exact methods and approximations will be compared from the accuracy point of view as well as for the computational effort.