*  Proportional hazards model
The generic term parametric proportional hazards models can be used to describe proportional hazards models in which the hazard ... Proportional hazards models are a class of survival models in statistics. Survival models relate the time that passes before ... For example, assuming the hazard function to be the Weibull hazard function gives the Weibull proportional hazards model. ... hazards models and Poisson regression models which is sometimes used to fit approximate proportional hazards models in software ...
*  Regression dilution
... and for some non-linear regression models. Other non-linear models, such as proportional hazards models for survival analysis, ... Hughes, M. D. (1993). "Regression dilution in the proportional hazards model". Biometrics. 49: 1056-1066. doi:10.2307/2532247. ... The case that x is fixed, but measured with noise, is known as the functional model or functional relationship. See, for ... In general, methods for the structural model require some estimate of the variability of the x variable. This will require ...
*  Customer attrition
Van Den Poel; Lariviére (2004). "Customer Attrition Analysis For Financial Services Using Proportional Hazard Models". European ... Several studies combine several different types of predictors to develop a churn model. This model can take demographic ... Since these models generate a small prioritized list of potential defectors, they are effective at focusing customer retention ... One of the main objectives of modeling customer churn is to determine the causal factors, so that the company can try to ...
*  Multicollinearity
"Customer attrition analysis for financial services using proportional hazard models". European Journal of Operational Research ... A principal danger of such data redundancy is that of overfitting in regression analysis models. The best regression models are ... Such a model is often called "low noise" and will be statistically robust (that is, it will predict reliably across numerous ... More importantly, the usual use of regression is to take coefficients from the model and then apply them to other data. Since ...
*  MedCalc
Survival analysis includes Cox regression (Proportional hazards model) and Kaplan-Meier survival analysis. Procedures for ...
*  Health effects of tobacco
Data reduction used Cox proportional hazard model, stratified by gender and country.) This compares to studies showing that ... Shihadeh A, Azar S, Antonios C, Haddad A (Sep 2004). "Towards a topographical model of narghile water-pipe café smoking: a ... A person's increased risk of contracting disease is directly proportional to the length of time that a person continues to ... but suppressed the findings or formatted them to imply lessened or no hazard. The term "smoker" is given to a person who ...
*  Semiparametric model
These models often use smoothing or kernels. A well-known example of a semiparametric model is the Cox proportional hazards ... a semiparametric model is a statistical model that has parametric and nonparametric components. A statistical model is a ... However, a semiparametric model is considered to be "smaller" than a completely nonparametric model because we are often ... It may appear at first that semiparametric models include nonparametric models, since they have an infinite-dimensional as well ...
*  Nested case-control study
"Methods for the Analysis of Sampled Cohort Data in the Cox Proportional Hazards Model". Annals of Statistics. 23 (5): 1749-1778 ... The analysis of a nested case control model must take into account the way in which controls are sampled from the cohort. ... Since the covariate is not measured for all participants, the nested case control model is both less expensive than a full ...
*  Hazard ratio
Survival analysis Failure rate and Hazard rate Proportional hazards models Odds ratio Relative risk Spruance, Spotswood; Julia ... Such models are generally classed proportional hazards regression models; the best known being the Cox semiparametric ... If the proportional hazard assumption holds, a hazard ratio of one means equivalence in the hazard rate of the two groups, ... proportional hazards model, and the exponential, Gompertz and Weibull parametric models. For two groups that differ only in ...
*  Accelerated failure time model
... that would be the proportional hazards model. Unlike proportional hazards models, in which Cox's semi-parametric proportional ... AFT model) is a parametric model that provides an alternative to the commonly used proportional hazards models. Whereas a ... Unlike proportional hazards models, the regression parameter estimates from AFT models are robust to omitted covariates. They ... proportional hazards model assumes that the effect of a covariate is to multiply the hazard by some constant, an AFT model ...
*  Kaplan-Meier estimator
... parametric survival models and the Cox proportional hazards model may be useful to estimate covariate-adjusted survival. The ...
*  Poisson regression
... creates proportional hazards models, one class of survival analysis: see proportional hazards models for ... Other generalized linear models such as the negative binomial model or zero-inflated model may function better in these cases. ... A Poisson regression model is sometimes known as a log-linear model, especially when used to model contingency tables. Negative ... This model is popular because it models the Poisson heterogeneity with a gamma distribution. Poisson regression models are ...
*  Log-rank test
The log-rank statistic can be derived as the score test for the Cox proportional hazards model comparing two groups. It is ... assume the hazard functions in the two groups are proportional with hazard ratio λ {\displaystyle \lambda } and d 1 {\ ... If the hazard ratio is λ {\displaystyle \lambda } , there are n {\displaystyle n} total subjects, d {\displaystyle d} is the ... The log-rank test statistic compares estimates of the hazard functions of the two groups at each observed event time. It is ...
*  Randomized controlled trial
Kaplan-Meier estimators and Cox proportional hazards models for time to coronary heart disease after receipt of hormone ... Vonesh, Edward F.; Chinchilli, Vernon G. (1997). "Crossover Experiments". Linear and Nonlinear Models for the Analysis of ...
*  Nancy Flournoy
Her work in this time on the graft-versus-tumor effect becoame "the first major application of the proportional hazards model ... for serving as a role model and mentor for graduate students and young faculty; for her scholarship in teaching and research, ...
*  Predictive modelling
Semiparametric regression includes the proportional odds model and the Cox proportional hazards model where the response is a ... The predictive modeling in trading is a modeling process wherein we predict the probability of an outcome using a set of ... The generalized linear model (GLM) is a flexible family of models that are unified under a single method. Logistic regression ... Uplift modelling is a technique for modelling the change in probability caused by an action. Typically this is a marketing ...
*  Predictive analytics
Some of the models commonly used are Kaplan-Meier and Cox proportional hazard model (non parametric). Globally-optimal ... Most models try to model the hazard rate by choosing the underlying distribution depending on the shape of the hazard function ... Model Monitoring : Models are managed and monitored to review the model performance to ensure that it is providing the results ... Modelling : Predictive modelling provides the ability to automatically create accurate predictive models about future. There ...
*  Cinnabar moth
An Analysis Based on the Proportional Hazards Model."Journal of Animal Ecology , Vol. 54, No. 3 (Oct., 1985). Coombs, E. M., et ...
*  Formica polyctena
An Analysis Based on the Proportional Hazards Model."Journal of Animal Ecology, Vol. 54, No. 3 (Oct., 1985). Helantera, Heikki ... F. polyctena is consistent with this model, with almost completely sterile workers that do not lay eggs. This is in contrast to ... Aubert and Richard proposed this social vaccination model, where they argue that if fellow nestmates groom an infected ant, ...
*  Compensation law of mortality
... proportional hazard models). The compensation law of mortality also represents a great challenge for many theories of aging and ... PMID 111909 Gavrilov, L.A. "A mathematical model of the aging of animals". Doklady Akademii Nauk SSSR, 1978, 238(2): 490-492. ...
*  Likelihood function
It is a key component of the proportional hazards model: using a restriction on the hazard function, the likelihood does not ... Model Selection and Multimodel Inference, §2.8 (Springer). Pawitan, Yudi (2001). In All Likelihood: Statistical Modelling and ... exp((AIC(M1) − AIC(M2))/2) To see that this is a generalization of the earlier definition, suppose that we have some model M ... "Generalized Linear Model - course notes". Tunghai University, Taichung, Taiwan. pp. Chapter 5. Retrieved 2017-10-01. Montoya, ...
*  Overfitting
For logistic regression or Cox proportional hazards models, there are a variety of rules of thumb (e.g. 5-9, 10 and 10-15 - the ... The book Model Selection and Model Averaging (2008) puts it this way. Given a data set, you can fit thousands of models at the ... An underfitted model is a model where some parameters or terms that would appear in a correctly specified model are missing. ... Model Selection and Model Averaging, Cambridge University Press . Harrell, F. E., Jr. (2001), Regression Modeling Strategies, ...
*  One in ten rule
... in particular proportional hazards models and logistic regression) without risk of overfitting. The rule states that one ... Chapter 8: Statistical Models for Prognostication: Problems with Regression Models at the Wayback Machine (archived October 31 ... Harrell, F. E. Jr.; Lee, K. L.; Mark, D. B. (1996). "Multivariable prognostic models: issues in developing models, evaluating ... Model building in Proc PHREG with automatic variable selection and information criteria. Paper 206-30 in SUGI 30 Proceedings, ...
*  David Cox (statistician)
... of which the best known is perhaps the proportional hazards model, which is widely used in the analysis of survival data. An ... Papers in honour of Sir David Cox on his 80th birthday ISBN 0-19-856654-9 Cox process Proportional hazards models Logrank test ... "the development of the Proportional Hazard Regression Model." In 2010 he was awarded the Copley Medal of the Royal Society "for ... Time series models in econometrics, finance and others (Chapman & Hall/CRC, 1996). With D. V. Hinkley and Ole E. Barndorff- ...
*  Ordinal regression
... which gives the proportional hazards model. The probit version of the above model can be justified by assuming the existence of ... as in the ordered logit/probit models. The prediction rule for this model is to output the smallest rank k such that wx < θk. ... gives the ordered logit model, while using the probit function gives the ordered probit model. A third option is to use an ... in the ordered logit and ordered probit models, propose fitting ordinal regression models by adapting common loss functions ...
*  UML state machine
This model of execution is called run to completion, or RTC. In the RTC model, the system processes events in discrete, ... As long as other state machines do not share variables or other resources with each other, there are no concurrency hazards. ... From experience in the trenches, the likelihood of such an architectural decay is directly proportional to the overhead (actual ... To model this behavior in a state machine without memory, you would need to introduce 1,000 states (e.g., pressing a key in ...