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Análise de dados categóricos de integridade celular de cianobactérias.

Clemente, Allan; Oliveira, Samylla; Menezes, Indira; Carloto, Ismael; Capelo Neto, Jos�


Allan Clemente

Samylla Oliveira

Ismael Carloto

Jos� Capelo Neto


The techniques used in cyanobacterial cell integrity/viability studies provide two outcomes: intact cells or not. These categorical and dichotomous values often make statistical analysis of the results difficult. In this context, the aim of this paper is to present two methodologies for the analysis of these data, showing a detailed sequence of procedures that allow analyzing, with the necessary statistical accuracy, categorized cell integrity data. For this, 3600-records database was used with the results of cellular integrity of Dc and Rr. Among the results, the traditional approach proved appropriate to identify the association between causes and effect respecting the specific characteristics of each species and the odds ratio (OR) calculation allowed to measure the associations. In this multivariate approach, the estimated OR requires a differentiated interpretation in relation to the traditional approach since the estimates are adjusted for the effect of all other variables of the model. The full text of this article is in Portuguese.


CLEMENTE, A., OLIVEIRA, S., MENEZES, I., CARLOTO, I. and CAPELO NETO, J. 2021. Análise de dados categóricos de integridade celular de cianobactérias. Revista DAE [online], 69(228), pages 205-224. Available from:

Journal Article Type Article
Acceptance Date Dec 12, 2019
Online Publication Date Dec 7, 2020
Publication Date Mar 31, 2021
Deposit Date May 2, 2022
Publicly Available Date May 2, 2022
Journal Revista DAE
Print ISSN 0101-6040
Electronic ISSN 2675-4959
Publisher SABESP (Companhia de Saneamento Básico do Estado de São Paulo S.A.)
Peer Reviewed Peer Reviewed
Volume 69
Issue 228
Pages 205-224
Keywords Fisher exact test; Odds ratio; Logistic binomial regression; Filamentous cyanobacteria; Cylindrospermopsis raciborskii; Dolichospermum circinale; Multivariate approach
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