• Regression Models
  • Multiple linear regression models were used to identify anthropometric, clinical, behavioral, and dietary factors associated with fasting insulin and glucose in a subcohort of non-diabetics in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (n=366). (pubmedcentralcanada.ca)
  • 1978). The case of multiple predictor variables subject to variability (possibly correlated) has been well-studied for linear regression, and for some non-linear regression models. (wikipedia.org)
  • Poisson regression models are generalized linear models with the logarithm as the (canonical) link function, and the Poisson distribution function as the assumed probability distribution of the response. (wikipedia.org)
  • subset
  • a missing-data filter function, applied to the model.frame, after any subset argument has been used. (psu.edu)
  • Since these models generate a small prioritized list of potential defectors, they are effective at focusing customer retention marketing programs on the subset of the customer base who are most vulnerable to churn. (wikipedia.org)
  • predictors
  • it makes a parametric assumption concerning the effect of the predictors on the hazard function, but makes no assumption regarding the nature of the hazard function λ( t ) itself. (springer.com)
  • That is, a multiple regression model with colinear predictors can indicate how well the entire bundle of predictors predicts the outcome variable, but it may not give valid results about any individual predictor, or about which predictors are redundant with respect to others. (wikipedia.org)
  • Generalized additive model is a smoothing method for multiple predictors that allows for non-parametric predictions. (wikipedia.org)
  • assumes
  • Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. (wikipedia.org)
  • probability
  • In many cases the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an email determining how likely that it is spam. (wikipedia.org)
  • In biostatistics, the researcher may be interested in trying to model the probability of a patient being diagnosed with a certain type of cancer based on knowing, say, the incidence of that cancer in his or her family. (wikipedia.org)
  • In business, the marketer may be interested in modelling the probability of an individual purchasing a product based on the price of that product. (wikipedia.org)
  • time
  • Other types of survival models such as accelerated failure time models do not exhibit proportional hazards. (wikipedia.org)
  • The accelerated failure time model describes a situation where the biological or mechanical life history of an event is accelerated. (wikipedia.org)
  • The proportional hazards model included time-dependent effects of herd-year-season contemporary group and parity by stage of lactation interaction, as well as time-independent effects of sire and age at first calving. (pubfacts.com)
  • Cox regression (or proportional hazards regression) is approach for examining the result of numerous variables upon the time a defined occasion takes to occur. (statshelponline.com)
  • In a Cox proportional hazards regression design, the procedure of impact is the risk rate, which is the threat of failure (i.e., the danger or possibility of suffering the occasion of interest), provided that the individual has actually made it through up to a particular time. (statshelponline.com)
  • These are understood as the sped up time failure models, and usually do not presume proportional hazards. (statshelponline.com)
  • Different models with selected time-dependent aspects of exposure such as intensity, duration, and time since cessation were considered. (biomedcentral.com)
  • The WC model with the superpopulation variance estimator provides an alternative analytical approach for estimating the effects of time-varying exposures with detailed history exposure information in case-control studies, especially if many subjects have time-varying exposure intensity over lifetime, and if only one control is available for each case. (biomedcentral.com)
  • The WC model consists in using age as the time axis and weighting cases and controls according to their case-control status and the age conditional probabilities of developing the disease in the source population. (biomedcentral.com)
  • The weights proposed in the WC model are therefore time-dependent and estimated from data of the source population. (biomedcentral.com)
  • A person's increased risk of contracting disease is directly proportional to the length of time that a person continues to smoke as well as the amount smoked. (wikipedia.org)
  • The instantaneous hazard rate is the limit of the number of events per unit time divided by the number at risk, as the time interval approaches 0. (wikipedia.org)
  • The difference between hazard-based and time-based measures is akin to the difference between the odds of winning a race and the margin of victory. (wikipedia.org)
  • For example, if the model concerns the development of a tumor, it means that all of the pre-stages progress twice as fast as for the unexposed individual, implying that the expected time until a clinical disease is 0.5 of the baseline time. (wikipedia.org)
  • Scoring models process a customer's credit history, loan application, customer data, etc., in order to rank-order individuals by their likelihood of making future credit payments on time. (wikipedia.org)
  • function
  • In many situations, either the form of the true hazard function is unknown or it is complex, so the Cox model has definite advantages. (springer.com)
  • This paper puts a focus on the hazard function of inter-trade durations to characterize the intraday trading process. (uni-konstanz.de)
  • We show, based on an exogenous information process, that the way traders aggregate information has implications for the shape of the hazard function. (uni-konstanz.de)
  • assess
  • The objectives of the proposed approach are: to provide a stress condition model for health monitoring, to assess the WT s maintenance strategies, and to provide recommendations on current maintenance schemes for future operations of the wind farm. (comillas.edu)
  • analytical
  • In most applications, involuntary reasons for churn are excluded from the analytical models. (wikipedia.org)
  • Deployment : Predictive model deployment provides the option to deploy the analytical results into everyday decision making process to get results, reports and output by automating the decisions based on the modelling. (wikipedia.org)
  • However, people are increasingly using the term to refer to related analytical disciplines, such as descriptive modeling and decision modeling or optimization. (wikipedia.org)
  • 1992
  • in a 1992 paper, Wei pointed out that the Buckley-James model has no theoretical justification and lacks robustness, and reviewed alternatives. (wikipedia.org)
  • predictor
  • They explain the survival inning accordance with one aspect under examination, however overlook the effect of other.An option approach is the Cox proportional hazards regression analysis , which works for both quantitative predictor variables and for categorical variables. (statshelponline.com)
  • Other non-linear models, such as proportional hazards models for survival analysis, have been considered only with a single predictor subject to variability. (wikipedia.org)
  • In statistics, multicollinearity (also collinearity) is a phenomenon in which one predictor variable in a multiple regression model can be linearly predicted from the others with a substantial degree of accuracy. (wikipedia.org)
  • The model is "simple" in that each has only one independent, or predictor, variable, and it is "binary" in that the dependent variable can take on only one of two values: cancer or no cancer, and purchase or does not purchase. (wikipedia.org)
  • variability
  • The reply to Frost & Thompson by Longford (2001) refers the reader to other methods, expanding the regression model to acknowledge the variability in the x variable, so that no bias arises. (wikipedia.org)
  • prediction
  • By deploying new technologies such churn prediction models coupled with effective retention programs, customer attrition could be better managed to stem the significant revenue loss from defecting customers. (wikipedia.org)
  • The log-rank test has been shown to be too permissive a test, allowing significant results for survivorship prediction models that have low accuracy. (wikipedia.org)
  • Nearly any regression model can be used for prediction purposes. (wikipedia.org)
  • methods
  • However, their usage is limited to those methods that use this type of modelling approach which can have several drawbacks. (wikipedia.org)