Abstract
Abstract This article adapts a standard method of multivariate analysis to a highly complex sampling design utilizing the method of balanced repeated replication for calculating valid and consistent estimates of variance. The example illustrates that by doing univariate tests to compare the mean height (or weight) of six year old white males to the mean height (or weight) of six year old Negro males, no significant differences are found between the two groups. However, the multivariate approach yields a significant result because the directions of the differences between two groups with respect to two positively correlated variables are reversed.
Keywords
Multivariate statisticsUnivariateStatisticsMultivariate analysis of varianceMultivariate analysisReplication (statistics)MathematicsAnalysis of varianceSampling (signal processing)Variance (accounting)Sample size determinationStandard errorSample (material)EconometricsComputer scienceChemistry
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Publication Info
- Year
- 1972
- Type
- article
- Volume
- 67
- Issue
- 340
- Pages
- 780-782
- Citations
- 28
- Access
- Closed
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Cite This
Gary G. Koch,
Stanley Lemeshow
(1972).
An Application of Multivariate Analysis to Complex Sample Survey Data.
Journal of the American Statistical Association
, 67
(340)
, 780-782.
https://doi.org/10.1080/01621459.1972.10481293
Identifiers
- DOI
- 10.1080/01621459.1972.10481293