Biomaterial Database

NHPPREG: a computer program for the analysis of nonhomogeneous Poisson process data with covariates. 1992

A Ciampi, and G Dougherty, and Z Lou, and A Negassa, and J Grondin

McGill University, Montreal Children's Hospital Research Institute, Canada.

A program written in C is described which finds maximum likelihood estimates of regression coefficients and other relevant parameters for a point process with covariates. The data are assumed to come from a Poisson point process and may be modelled, at the user's choice, either totally parametrically or semi-parametrically. Furthermore, extra Poisson variation may be introduced, in both the parametric and semi-parametric approach, by the device of random effects. The work closely follows the theory developed by Lawless (1987).

UI	MeSH Term	Description	Entries
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012984	Software	Sequential operating programs and data which instruct the functioning of a digital computer.	Computer Programs,Computer Software,Open Source Software,Software Engineering,Software Tools,Computer Applications Software,Computer Programs and Programming,Computer Software Applications,Application, Computer Software,Applications Software, Computer,Applications Softwares, Computer,Applications, Computer Software,Computer Applications Softwares,Computer Program,Computer Software Application,Engineering, Software,Open Source Softwares,Program, Computer,Programs, Computer,Software Application, Computer,Software Applications, Computer,Software Tool,Software, Computer,Software, Computer Applications,Software, Open Source,Softwares, Computer Applications,Softwares, Open Source,Source Software, Open,Source Softwares, Open,Tool, Software,Tools, Software
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016012	Poisson Distribution	A distribution function used to describe the occurrence of rare events or to describe the sampling distribution of isolated counts in a continuum of time or space.	Distribution, Poisson
D016013	Likelihood Functions	Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.	Likelihood Ratio Test,Maximum Likelihood Estimates,Estimate, Maximum Likelihood,Estimates, Maximum Likelihood,Function, Likelihood,Functions, Likelihood,Likelihood Function,Maximum Likelihood Estimate,Test, Likelihood Ratio
D016019	Survival Analysis	A class of statistical procedures for estimating the survival function (function of time, starting with a population 100% well at a given time and providing the percentage of the population still well at later times). The survival analysis is then used for making inferences about the effects of treatments, prognostic factors, exposures, and other covariates on the function.	Analysis, Survival,Analyses, Survival,Survival Analyses