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Jackknifing in Categorical Data Analysis
Author(s) -
Parr William C.,
Tolley H. Dennis
Publication year - 1982
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.1982.tb00808.x
Subject(s) - jackknife resampling , categorical variable , multinomial distribution , mathematics , statistics , function (biology) , evolutionary biology , estimator , biology
Summary Estimation of nonlinear functions of a multinomial parameter vector is necessary in many categorical data problems. The first and second order jackknife are explored for the purpose of reduction of bias. The second order jackknife of a function g(.) of a multinomial parameter is shown to be asymptotically normal if all second order partials ∂ 2 g( p )∂dp i ∂ p j obey a Hölder condition with exponent α>1/2. Numerical results for the estimation of the log odds ratio in a 2times2 table demonstrate the efficiency of the jackknife method for reduction of mean‐square‐error and the construction of approximate confidence intervals.