2002
DOI: 10.1590/s0102-311x2002000300003
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Técnicas de análise de sobrevida

Abstract: Statistical methods known as survival analyses are useful for analyzing time-related events, in which time from a benchmark event to an endpoint is the focus of interest. Survival analysis describes not only patient survival statistics (as suggested by the name), but also other dichotomous outcomes such as time of remission, time of breastfeeding, etc. This paper discusses survival analysis techniques, commenting and comparing their utilization, especially in the field of oncology. It also presents and discuss… Show more

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Cited by 64 publications
(64 citation statements)
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References 27 publications
(35 reference statements)
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“…The final model included women who remained statistically significant (p < 0.05). We used the likelihood-ratio test to verify the significance of the parameters of the reduced models and Schoenfeld's residual diagnosis test to assess the proportionality of Cox models 22 . Input and descriptive analysis of data were conducted in the Statistical Package for the Social Sciences (SPSS) program, version 15.0, and we used the STATA program, version 12.0, to analyze survival and prognostic factors.…”
Section: Methodsmentioning
confidence: 99%
“…The final model included women who remained statistically significant (p < 0.05). We used the likelihood-ratio test to verify the significance of the parameters of the reduced models and Schoenfeld's residual diagnosis test to assess the proportionality of Cox models 22 . Input and descriptive analysis of data were conducted in the Statistical Package for the Social Sciences (SPSS) program, version 15.0, and we used the STATA program, version 12.0, to analyze survival and prognostic factors.…”
Section: Methodsmentioning
confidence: 99%
“…Associations were also investigated for the exposure variables using chi-square (χ 2 ) or Fisher's exact test, as appropriate 16 . Graphs using the Kaplan-Meier technique were produced to visualize the survival trend of IDUs between the field testing and the AIDS diagnosis 17 . Epidemiologically relevant exposure factors or those with a p-value of ≤ 0.20 were selected for multivariate analysis using the Cox proportional model, aimed at producing a model adjusted for confounding variables 18 .…”
Section: Methodsmentioning
confidence: 99%
“…(as suggested by the term "survival"), but also other events with dichotomous outcomes [35]. In this study, the final event assessed was the occurrence of bacterial infiltration.…”
Section: Discussionmentioning
confidence: 99%