Applied Survival Analysis: Regression Modeling of Time-to-Event Data
By David W. Hosmer Jr., S. Lemeshow, S. May. 2008
3,134 citations recorded by the source corpus.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/836192fb39196b7b3c1e3fb5b9b21bb75036a714
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Citations in the corpus
- Censored Quantile Regression Redux (2008, methodology): “To illustrate this technique we estimate the model appearing in (Portnoy 2003, Section 6.3), adapted from Hosmer and Lemeshow (1999), using the R code fragment: R> require("quantreg") R> data("uis") R> fit - crq(Surv(log(TIME), CENSOR) ~ ND1 + ND2 + IV3 + TREAT + FRAC + RACE + AGE * SITE, data =…”
- Survival dynamics of scleractinian coral larvae and implications for dispersal (2008, positive): “Such effects can be explicitly incorporated in parametric models in a manner analogous to random effects in standard linear statistical models (Hosmer and Lemeshow 1999).”
- Examining the influence of service additions on manufacturing firms' bankruptcy likelihood (2017, methodology): “Hosmer et al. (1999) propose a method to purposefully select variables for a logistic model.”
- Prior Occupational Experience, Anticipatory Socialization, and Employee Retention (2006, methodology): “Using the Wald test to evaluate the significance of the interaction term, all timedependent interaction variables for the model were found to be nonsignificant, thus ensuring the proportional-hazards assumption was met for the variables used in the analysis (Hosmer & Lemeshow, 1999).”