An Introduction to Survival Analysis using Stata

By Thomas Lumley. 2005

893 citations recorded by the source corpus.

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Citations in the corpus

Oil and political survival (2013, background): “Given that the proper distributional assumptions are made, parametric analysis is more e¢ cient than non-parametric- or semi-parametric models because prospective periods without leadership failures are also informative (Cleves et al., 2002).”
Inverted-U relationship between R&D intensity and survival : evidence on scale and complementarity effects in UK data. (2016, methodology): “Deviations from the 45◦ line at large values of time are to be expected (Cleves et al., 2008).”
A Survival Analysis of Islamic and Conventional Banks (2016, positive): “We use Efron's (1977) approximation to compromise between speed and accuracy (Cleves et al. 2010).”
Coordinating and competing in ecosystems: How organizational forms shape new technology investments (2013, methodology): “The Efron method is computationally more intensive than the Breslow method but performs a more accurate approximation (Cleves, Gould, and Gutierrez, 2008).”
Further Development of Flexible Parametric Models for Survival Analysis (2009, methodology): “Delayed entry is also needed when incorporating time-dependent covariates or piecewise time-dependent effects similarly to the Cox model (Cleves et al. 2008).”
Loneliness, Health, and Mortality in Old Age: A National Longitudinal Study (2012, neutral): “The parametric models produced more efficient estimates than semiparametric (Cox) hazard models (Cleves et al., 2008), and the Weibull distribution was the most efficient and parsimonious functional form for our sample data based on the Akaike Information Criterion.”
Oil and the duration of dictatorships (2011, neutral): “We will specify the survival of dictators by means of a standard (parametric) proportional hazard model (see e.g. Kalbfleisch and Prentice 2002, Cleves, Gould and Gutierrez 2004) , which is given by h ic (t|x ic ) = h 0 (t) exp(x ic β x ), (8) where h ic is the hazard a dictator i faces in a…”
The transition from higher education to employment in Europe: the analysis of the time to obtain the first job (2007, neutral): “For technical details, see Cleves et al. (2002) and Gutierrez (2002).”
Signaling in Equity Crowdfunding (2015, neutral): “Survival analysis has the advantage over other regression techniques that it allows the distribution of time-to-event to be non-normal as well as for censored data (Cleves et al., 2008).”
Should We Stay or Should We Go? Accountability, Status Anxiety, and Client Defections (2006, positive): “Second, I reestimated the full model again using a “shared frailty model,” which allows heterogeneity between firms located in different counties by incorporating a group (county) effect that follows a gamma distribution with a mean of one and a variance of (Cleves, Gould, and Gutierrez, 2002).”
Why Family Matters: The Impact of Family Resources on Immigrant Entrepreneurs’ Exit from Entrepreneurship (2016, neutral): “Second, we estimated frailty models 14 , which introduce a gamma distributed random effect (i.e., “frailty”) into the Cox model to control for unobserved heterogeneity – that is, whether individuals differ in unobserved ways in their inherent probability of failure (Cleves et al., 2008).”
Real options and foreign affiliate divestments: A portfolio perspective (2009, background): “…on the proportional change in the single period divestment hazard (exp(xb)) and lend themselves to a direct interpretation as an elasticity (e.g. Cleves et al, 2004; Wooldridge, 2002), we also calculated the cross effect of uncertainty on the elasticity of the hazard with respect to labor cost…”
Risky Business? Entrepreneurship in the New Independent-Power Sector (2005, methodology): “We used a Stata utility, the link test, to verify adequate parameterization of our models (Cleves, Gould, and Gutierrez, 2002).”
Staying Power: What Influences Micro-firm Survival in Tourism? (2013, neutral): “Calculations are made at every time point, allowing a richer analysis of data (see Cleves et al. (2004) for a guide to survival analysis).”