###### **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 ...