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A NOTE ON COMPETING VARIANCE ESTIMATORS IN RANDOMISED RESPONSE SURVEYS
Author(s) -
Chaudhuri Arijit,
Maiti Tapabrata,
Roy Debesh
Publication year - 1996
Publication title -
australian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 0004-9581
DOI - 10.1111/j.1467-842x.1996.tb00361.x
Subject(s) - estimator , variance (accounting) , statistics , confidence interval , econometrics , usable , population , construct (python library) , population variance , regression analysis , regression , variable (mathematics) , mathematics , computer science , demography , economics , sociology , mathematical analysis , accounting , world wide web , programming language
SUMMARY When gathering randomised rather than direct responses on a variable of interest relating to sensitive issues, one may use a modified version of the well‐known generalised regression predictor of a finite population total. To construct confidence intervals, this paper proposes four alternative variance estimators – modifications to those usable with direct responses – and examines their relative efficiencies through simulations from simple super‐population models.