Test of association: which one is the most appropriate for my study?

Gonzalez-Chica, David Alejandro; Bastos, João Luiz; Duquia, Rodrigo Pereira; Bonamigo, Renan Rangel; Martínez-Mesa, Jeovany

doi:10.1590/abd1806-4841.20154289

Acessibilidade / Reportar erro

Brasil

Anais Brasileiros de Dermatologia

Español English

Brasil

Español English

sumário « anterior atual seguinte »

Sumário

Epidemiology and Biostatistics Applied to Dermatology • An. Bras. Dermatol. 90 (4) • Jul-Aug 2015 • https://doi.org/10.1590/abd1806-4841.20154289 copy

Test of association: which one is the most appropriate for my study?^* * Study conducted at the Federal University of Santa Catarina (UFSC) - Florianópolis (SC), Brazil.

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

BACKGROUND:

Hypothesis tests are statistical tools widely used for assessing whether or not there is an association between two or more variables. These tests provide a probability of the type 1 error (p-value), which is used to accept or reject the null study hypothesis.

OBJECTIVE:

To provide a practical guide to help researchers carefully select the most appropriate procedure to answer the research question. We discuss the logic of hypothesis testing and present the prerequisites of each procedure based on practical examples.

Keywords:
Data analysis; Association; Epidemiology and biostatistics; Hypothesis testing; Statistical methods and procedures

Parameter	Interpretation	What is it for?
Correlation coefficient (r)^* * "r" values should not be interpreted as "strength" of association, given that different slopes in the prediction line (different β values, indicating different strength of association) may have the same "r" value	Measurement of linear relationship between two numeric variables, which can be positive (as one variable increases the other variable also increases) or negative (as one variable increases the other variable decreases).	It measures the extent to which the "observed" values approximate the prediction line. It provides information on the direction of association between the variables
Intercept (α)	Outcome value when the exposure value is zero	It serves to fit an imaginary horizontal line, which is necessary to estimate β
Linear regression coefficient (β)	It represents how much the outcome changes (increase or decrease) with each one-unit increment in the exposure variable.	It determines the prediction line slope in relation to the horizontal line fit by α. It provides information on the direction of association between the variables, as well as on the strength (intensity) of this relationship

Sociedade Brasileira de Dermatologia Av. Rio Branco, 39 18. and., 20090-003 Rio de Janeiro RJ, Tel./Fax: +55 21 2253-6747 - Rio de Janeiro - RJ - Brazil
E-mail: revista@sbd.org.br

Acompanhe os números deste periódico no seu leitor de RSS

[1] MAILING ADDRESS: David Alejandro Gonzalez-Chica, Departamento de Nutrição, Centro de Ciências da Saúde, Universidade Federal de Santa Catarina, Trindade, 88040-970 - Florianópolis - SC, Brazil. E-mail: david.epidemio@gmail.com

	A. Observed values Use sunscreen at the beach (Outcome)


Gender (Exposure)	No	Yes	Total
Gender (Exposure)
Male	255	195	450
Female	102	359	461
Total	357	554	911
	B. Expected Values Use sunscreen at the beach (Outcome)


Gender (Exposure)	No	Yes	Total
Gender (Exposure)
Male	176	274	450
Female	181	280	461
Total	357	554	911
Test result = 114; Degrees of freedom = 1; P-value <0.001

Brasil

Brasil

Test of association: which one is the most appropriate for my study?* * Study conducted at the Federal University of Santa Catarina (UFSC) - Florianópolis (SC), Brazil.

Abstract

BACKGROUND:

OBJECTIVE:

Test of association: which one is the most appropriate for my study?^* * Study conducted at the Federal University of Santa Catarina (UFSC) - Florianópolis (SC), Brazil.