Sampling procedures and calculation for sample size determination: criteria and methods adopted in theses and dissertations in Human Movement Sciences - a descriptive study

• Autor(a) principal: Costa, Rochelle Rocha
• Data de Publicação: 2018
• Outros Autores: Backes, Othavio Porto, Figueiredo, Pedro, Castro, Flávio Antônio de Souza
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista Brasileira de Cineantropometria & Desempenho Humano (Online)
• Texto Completo: https://periodicos.ufsc.br/index.php/rbcdh/article/view/51178

Quantitative monographic studies systematically use inferential statistical procedures to test hypotheses. For this purpose, sampling procedures and sample sizes need to be adequate for the proposed procedures. The aim of this study was to identify the sample selection methods, as well as the performance and types of calculation to determine the sample size adopted in theses and dissertations developed in a graduate program in the field of Physical Education. Theses and dissertations defended between 2003 and 2013 were obtained through digital repository. Only quantitative studies were included, in which the following issues were analyzed: (1) sample selection criteria; (2) presence of sample calculation; (3) calculation type to estimate sample size. A total of 199 studies were included. Of these, 6% (n=11) used probabilistic methods for sample selection and 3% (n=6) used animal models. As for the accomplishment of sample calculations, 36% (n=72) studies reported having adopted this procedure. Of studies that performed sample calculations, 25% (n=18) used predictive equations, 67% (n=48) considered methods with statistical power as their base, 3% (n=2) used confidence interval, 4% (n=3) did not mention the method and 1% (n=1) was based on the type of statistical test to be used later. Nonprobabilistic sampling methods predominate for the selection of subjects; most studies do not report adopting calculations to estimate sample size and, among those that reported the use, the models that consider statistical power as the main criterion are predominant.