TY - JOUR

T1 - Perturbation by multiplicative noise and the Simulation Extrapolation method

AU - Biewen, Elena

AU - Nolte, Sandra

AU - Rosemann, Martin

PY - 2008/12

Y1 - 2008/12

N2 - While most of the literature on measurement error focuses on additive measurement error, we consider in this paper the multiplicative case. We apply the Simulation Extrapolation method (SIMEX)—a procedure which was originally proposed by Cook and Stefanski (J. Am. Stat. Assoc. 89:1314–1328, 1994) in order to correct the bias due to additive measurement error—to the case where data are perturbed by multiplicative noise and present several approaches to account for multiplicative noise in the SIMEX procedure. Furthermore, we analyze how well these approaches reduce the bias caused by multiplicative perturbation. Using a binary probit model, we produce Monte Carlo evidence on how the reduction of data quality can be minimized.

AB - While most of the literature on measurement error focuses on additive measurement error, we consider in this paper the multiplicative case. We apply the Simulation Extrapolation method (SIMEX)—a procedure which was originally proposed by Cook and Stefanski (J. Am. Stat. Assoc. 89:1314–1328, 1994) in order to correct the bias due to additive measurement error—to the case where data are perturbed by multiplicative noise and present several approaches to account for multiplicative noise in the SIMEX procedure. Furthermore, we analyze how well these approaches reduce the bias caused by multiplicative perturbation. Using a binary probit model, we produce Monte Carlo evidence on how the reduction of data quality can be minimized.

KW - Errors-in-variables in nonlinear models

KW - Disclosure limitation methods

KW - Multiplicative error

KW - Simulation extrapolation method

U2 - 10.1007/s10182-008-0089-7

DO - 10.1007/s10182-008-0089-7

M3 - Journal article

VL - 92

SP - 375

EP - 389

JO - AStA Advances in Statistical Analysis

JF - AStA Advances in Statistical Analysis

SN - 1863-8171

IS - 4

ER -