Applied Survival Analysis: Regression Modeling of Time to Event Data

By Pallipamu Venkateswara Rao, David W. Hosmer Jr., S. Lemeshow. 2000

1,345 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8d372a9d7d71fc923c638d504b06729e1af648b1

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Citations in the corpus

Temporal and spatial modelling of tropical deforestation: a survival analysis linking satellite and household survey data (2002, methodology): “likelihood methods, with the assumption that the underlying survival models is distributed as type I extreme value (Irwin, 1998; Hosmer and Lemeshow, 1999).”
A New Log-location Regression Model with Influence Diagnostics and Residual Analysis (2018, methodology): “This data set is reported in Hosmer and Lemeshow [19] and can also be found in R package Bolstad2.”
The Goldilocks Effect: Human Infants Allocate Attention to Visual Sequences That Are Neither Too Simple Nor Too Complex (2012, methodology): “An appropriate model for this kind of data–used primarily in biostatistics to study, for example, predictors of mortality–is known as a survival analysis [30,31].”
DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network (2016, methodology): “Worcester Heart Attack Study (WHAS) The Worcester Heart Attack Study (WHAS) investigates the effects of a patient’s factors on acute myocardial infraction (MI) survival [27].”
Survival Analysis Part I: Basic concepts and first analyses (2003, methodology): “The logrank method is considered more robust (Hosmer and Lemeshow, 1999), but the lack of an accompanying effect size to compliment the P-value it provides is a limitation.”
Censored Regression Quantiles (2003, background): “The following example, taken from the text of Hosmer and Lemeshow (1999), concerns the comparison of two courses of treatments for drug abuse (“long” D 1 and “short” D 0).”
Amplified predation after fire suppresses rodent populations in Australia’s tropical savannas (2016, methodology): “TheCox proportional hazards regressionmodel, implemented in the ‘survival’ package of R, was used to analyse the distribution of survival times of radio-tracked R. tunneyi individuals (Hosmer et al. 2008).”
Multi-omic and multi-view clustering algorithms: review and cancer benchmark (2018, methodology): “First, we measured differential survival between the obtained clusters using the logrank test (106).”
Biological control of thrips and whiteflies by a shared predator: Two pests are better than one (2008, methodology): “Kaplan–Meier survival curves on different diets were fitted and compared using the log-rank test (Hosmer and Lemeshow 1999, library survival, R Development Core Team, 2005).”
Pancreatic neuroendocrine tumors (PNETs): incidence, prognosis and recent trend toward improved survival. (2008, neutral): “Multivariate Cox regression models were used to estimate hazard ratios for sex, age, race, stage, and functional status [13].”
Intraseasonal climate and habitat‐specific variability controls the flowering phenology of high alpine plant species (2010, methodology): “To examine the synchronizing effect of the environmental factors TS, SMand PHonplant phenology, parametric time-to-eventmodels for interval censored data (Hosmer & Lemeshow 1999; Klein & Möschberger 2003) were used.”