2000
DOI: 10.1007/978-1-4612-1304-8
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Analysis of Multivariate Survival Data

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Cited by 1,166 publications
(1,082 citation statements)
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“…For this purpose, episodes were analyzed as recurrent events using a gamma frailty model. 16 All tests, except for the analysis of the primary end point, were 2 sided. P values <0.05 were considered statistically significant.…”
Section: Discussionmentioning
confidence: 99%
“…For this purpose, episodes were analyzed as recurrent events using a gamma frailty model. 16 All tests, except for the analysis of the primary end point, were 2 sided. P values <0.05 were considered statistically significant.…”
Section: Discussionmentioning
confidence: 99%
“…Standard descriptive and non-parametric comparative statistics were used to characterise and compare groups. The number of severe hypoglycaemic episodes and the number of severe hypoglycaemic episodes with coma were analysed by a frailty model for recurrent events (an extension of the log-linear Poisson model including a gamma-distributed variation between patients) that takes into account the highly skewed distribution of events of severe hypoglycaemia [18]. The effect of an explanatory factor is reported as relative risk with 95% confidence limits.…”
Section: Methodsmentioning
confidence: 99%
“…This is the approach I now recommend for analysing survival data for AB/BA cross-over trials. However, such methods do not readily generalize to more complex designs and it may be worth studying Philip Hougaard's magnificent book on multivariate survival analysis [31] for alternatives. …”
Section: Time-to-event Analysismentioning
confidence: 99%