[Estimate methods used with complex sampling designs: their application in the Cuban 2001 health survey].

Objectives: To look at the individual features of three different methods used to estimate simple parameters--means, totals, and percentages, as well as their standard errors--and of logistic regression models, and to describe how such methods can be used for analyzing data obtained from complex samples.

Methods: Data from Cuba's Second National Survey of Risk Factors and Non-Communicable Chronic Ailments [Segunda Encuesta Nacional de Factores de Riesgo y Afecciones Crónicas No Transmisibles], which was conducted in 2001, were studied. A complex, stratified multi-stage cluster sampling design was used.

[Influence of data structure on the selection of statistic analysis methods].

In medical research, data is grouped either as per the design of the study or the selection of the sample. This structure must be taken into account in order to make correct estimates of the of the parameters and standard errors involved. This study is of the methodological type and is aimed at illustrating methods for estimating population-related methods and regression models with grouped data.