Statistical Models and Methods for Lifetime Data

Technometrics, 2003

3,150 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e4a86a2caf9d997e4043d5ae4372b1a0ae310db2

Citations in the corpus

• A Skewed Sinh-Normal Distribution and Its Properties and Application to Air Pollution (2010, methodology): “This class of models is called accelerated failure time regression; see Lawless ( 2002 , Ch.”
• A new generalized p-value approach for testing equality of coefficients of variation in k normal populations (2011, positive): “According to Rao [18] and Lawless [19], [U(θ̃)]′I−1(θ̃)U(θ̃) is approximately distributed as χ2(k − 1).”
• Visual Tracking: an Experimental Survey (2013, neutral): “These types of plots are referred to as survival curves [109], a terminology borrowed from medicine to test the effectiveness of treatments on patients [110].”
• Maximum likelihood estimation under a finite mixture of generalized exponential distributions based on censored data (2012, background): “For more details about the analysis of censored failure times and type-I and type-II censoring, see Kalbfleisch and Prentice (1980) and Lawless (1982).”
• Generating survival times to simulate Cox proportional hazards models (2005, methodology): “The density and survival function of the extreme value distribution with parameters λ and α are given by [21]”
• A Bayes analysis of modified Weibull distribution via Markov chain Monte Carlo simulation (2010, background): “Its suitability is well established in a number of situations ranging from reliability testing to biomedical applications, etc. (see, e.g., Mann et al. [1], Lawless [2], Nelson [3], Murthy et al. [4] among others).”
• First in, First out? The Effects of Network Externalities on Pioneer Survival (2004, methodology): “The AFT method is well accepted in the fields of statistics, engineering, and sociology (see Allison 1995; Kalbfleisch and Prentice 1980; Lawless 1982) but has been used infrequently in marketing (e.g., Bayus 1998; Manchanda et al. 2002).”
• Response‐adaptive randomization for survival trials: the parametric approach (2007, background): “These models belong to the log-location–scale family (Lawless, 2002).”
• A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation (2008, methodology): “Maximum likelihood fitting of Gumbel and exponential distributions is implemented in the gumbel and exponential modules of Easel, respectively, following methods in [46].”
• Threshold Regression for Survival Analysis: Modeling Event Times by a Stochastic Process Reaching a Boundary (2006, methodology): “Likewise, Lawless (2003) gives a complete and compact summary of theory, models and methods (see Section 11.5, pages 518–523).”
• Prevalence, incidence, survival, and disease characteristics of systemic sclerosis in a large US population. (2003, methodology): “Survival time comparisons, adjusted for age at diagnosis, were performed using left-truncated Cox proportional hazards regression (27,28).”
• Objective Priors for Discrete Parameter Spaces (2012, methodology): “Lawless (1982), Section 1.4), where there is a sample of N units whose lifetimes follow an exponential distribution with mean 1/λ. • The experiment is stopped as soon as R units have failed; • Let t1 ≤ · · · ≤ tR denote the resulting failure times. Here N ≥ R and λ are both unknown, while R is pre-s”
• A new lifetime model: the Kumaraswamy generalized Rayleigh distribution (2014, background): “Lawless [17] reported an experiment in which specimens of solid epoxy electrical insulation were studied in an accelerated voltage life test.”