Doctoral Thesis
DOI
10.11606/T.5.2009.tde-22022010-175431
Document
Author
Full name
Euro de Barros Couto Junior
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2009
Supervisor
Committee
Azevedo Neto, Raymundo Soares de (President)
Carvalho, Heraclito Barbosa de
Martins, Lourdes Conceição
Silva, Nilza Nunes da
Silveira, Paulo Sergio Panse
Title in Portuguese
Abordagem não-paramétrica para cálculo do tamanho da amostra com base em questionários ou escalas de avaliação na área de saúde
Keywords in Portuguese
Amostragem
Estatística não paramétrica
Lógica
Matemática
Saúde
Tamanho da amostra
Abstract in Portuguese
Title in English
Non-parametric approach for calculation of sample size based on questionnaires or scales of assessment in the health care
Keywords in English
Data collection
Health
Logic
Mathematics
Nonparametric statistics
Sample size
Sample studies
Abstract in English
This text suggests how to calculate a sample size based on the use of a data collection instrument consisting of categorical items. The arguments for this suggestion are based on theories of Combinatorics and Paraconsistency. The purpose is to suggest a practical and simple calculation procedure to obtain an acceptable sample size to collect information, organize it and analyze data from an application of an instrument for collecting medical data, based exclusively on discrete items (categorical items), i.e., each item of the instrument is considered as a non-parametric variable with finite number of categories. In the health care it is very common to use survey instruments on the basis of such items: clinical protocols, hospital registers, questionnaires, scales and other tools for hearing consider a sequence of items organized categorically. A formula for calculating the sample size was proposed for a population of unknown size, and an adjusted formula has been proposed for population of known size. It was seen, with practical examples, the possibility of using both formulas, allowing to consider the practicality of the use in cases that have little or no information available about the population from which the sample is collected