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Certain aspects of the multivariate analysis of data from possibly complex survey designs are discussed in terms of a large sample methodology involving weighted least squares algorithms for the computation of Wald statistics. In particular, consideration is given to the problems associated with univariate and multivariate comparisons among cross-classified sub-populations. Finally, a philosophical discussion based on response (in the sense of measurement) error model concepts is given to motivate the validity of such least squares (both unweighted and weighted) methods for investigating the relationship between a particular dependent variable and several independent variables in a manner analogous to multiple regression analysis. This methodology is illustrated with several examples involving data from reports of the U.S. National Center for Health Statistics. /// Cet article discute de certains aspects de l'analyse multi-variate des données provenant de plans d'enquête éventuellement complexes, en terme de la méthodologie des grands échantillons, incluant les algorithmes des moindres carrés pondérés pour le calcul des statistiques de Wald. Une attention particulière est donnée aux problèmes associés aux comparaisons à une ou plusieurs variables dans les sous-populations croisées. Enfin, une discussion philosophique basée sur les résultats (au sens de la mesure) des concepts de modèle avec erreur, est engagée, en vue de légitimer la validité des méthodes des moindres carrés (pondérés ou non) dans l'étude de la relation entre une variable dépendante particulière et plusieurs variables indépendantes d'une manière analogue à l'analyse de régression multiple. Cette méthodologie est illustrée par plusieurs exemples portant sur des données contenues dans l'U.S. National Center for Health Statistics.
The International Statistical Review (ISR) is the flagship journal of the International Statistical Institute and of its constituent sections (the Bernoulli Society for Mathematical Statistics and Probability, the International Association for Official Statistics, the International Association for Statistical Computing, the International Association for Statistical Education, the International Association of Survey Statisticians and the International Society for Business and Industrial Statistics). The ISR is widely circulated and subscribed to by individuals and institutions in all parts of the world. The main aim of the ISR is to publish papers of an expository, review, or tutorial nature that will be of wide interest to readers. Such papers may or may not contain strictly original material. All papers are refereed.
Established in 1885, the International Statistical Institute (ISI) is one of the oldest scientific associations operating in the modern world. Its success can be attributed to the increasing worldwide demand for professional statistical information, its leadership in the development of statistical methods and their application, and in the collective dedication of its members. Our influence can be seen in the improvements in information and analysis throughout the economic, social, biological and industrial sectors. Its industrial influence is evidenced in advanced statistical practises, resulting in improved quality assurance. The ISI is also proud of its continuing support of statistical progress in the developing world. The ISI is composed of more than 2,000 individual elected members who are internationally recognised as the definitive leaders in the field of statistics. Its membership crosses all borders, representing more than 133 countries worldwide. This reservoir of expertise is supplemented by approximately 3,000 + additional individual members of the Institute's specialised sections: The Bernoulli Society for Mathematical Statistics and Probability (BS) The International Association for Official Statistics (IAOS) The International Association for Statistical Computing (IASC) The International Association for Statistical Education (IASE) The International Association of Survey Statisticians (IASS) The International Society for Business and Industrial Statistics (ISBIS) Irving Fisher Society for Financial and Monetary Statistics (ISI transitional Section) The ISI publishes a variety of professional books, journals, newsletters and reports, representing the cutting edge in the development of contemporary statistical knowledge. The ISI is especially renowned for its biennial meetings in which the entire membership congregates to exchange innovative ideas, develop new links and discuss current trends and developments in the statistical world.
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© 1975 International Statistical Institute (ISI)