Chi-Squared Tests with Complex Survey Data Subject to Misclassification Error

Author(s):  
J. N. K. Rao ◽  
D. Roland Thomas
Author(s):  
Phillip S. Kott

Coverage intervals for a parameter estimate computed using complex survey data are often constructed by assuming the parameter estimate has an asymptotically normal distribution and the measure of the estimator’s variance is roughly chi-squared. The size of the sample and the nature of the parameter being estimated render this conventional “Wald” methodology dubious in many applications. I developed a revised method of coverage-interval construction that “speeds up the asymptotics” by incorporating an estimated measure of skewness. I discuss how skewness-adjusted intervals can be computed for ratios, differences between domain means, and regression coefficients.


2010 ◽  
Vol 22 ◽  
pp. 129-158 ◽  
Author(s):  
Liming Cai ◽  
Mark Hayward ◽  
Yasuhiko Saito ◽  
James Lubitz ◽  
Aaron Hagedorn ◽  
...  

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