weightedScores: Weighted Scores Method for Regression Models with Dependent Data. Has functions that handle the steps for the weighted scores method in Nikoloulopoulos, Joe and Chaganty (2011, Biostatistics, 12: 653-665) for binary (logistic and probit), Poisson and negative binomial regression, with dependent data. Two versions of negative binomial regression from Cameron and Trivedi (1998) are used. Let NB(tau,xi) be a parametrization with probability mass function f(y; tau, xi) = Gamma(tau + y) xi^y / [ Gamma(tau) y! (1 + xi)^( tau + y )], for y = 0, 1, 2, ... , tau > 0 , xi > 0, with mean mu = tau*xi = exp(beta^T x) and variance tau*xi*(1 + xi), where x is a vector of covariates. For NB1, the parameter gamma is defined so that tau=mu/gamma, xi=gamma; for NB2, the parameter gamma is defined so that tau=1/gamma, xi=mu*gamma. In NB1, the convolution parameter tau is a function of the covariate x and xi is constant; in NB2, the convolution parameter tau is constant and xi is a function of the covariate x.
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References in zbMATH (referenced in 6 articles )
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- Dey, Rajib; Islam, M.Ataharul: A conditional count model for repeated count data and its application to GEE approach (2017)
- Cattelan, Manuela; Varin, Cristiano: Hybrid pairwise likelihood analysis of animal behavior experiments (2013)
- Nikoloulopoulos, Aristidis K.: Copula-based models for multivariate discrete response data (2013)
- Nikoloulopoulos, Aristidis K.: On the estimation of normal copula discrete regression models using the continuous extension and simulated likelihood (2013)
- Masarotto, Guido; Varin, Cristiano: Gaussian copula marginal regression (2012)
- Nikoloulopoulos, Aristidis K.; Joe, Harry; Rao Chaganty, N.: Weighted scores method for regression models with dependent data (2011)