EffectsEst.multiroot: Maximum likelihood estimation of the fixed and random effects...

In idaejin/PROreg: Patient Reported Outcomes Regression Analysis

Description

EffectsEst.multiroot function performs a maximum likelihood estimation of the fixed and random effects in a beta-binomial mixed-effects model given some initial values.

It uses the multiroot function of the rootSolve R-package.

Usage

EffectsEst.multiroot(y,m,beta,u,phi,D.,X,Z)

Arguments

y	dependent response variable in the model.
m	maximum score number in each beta-binomial observation.
beta	initial values of the fixed-effects.
u	initial values of the random-effects.
phi	estimated value of the dispersion parameter of the beta-binomial distribution.
D.	estimated value of the variance-covariance matrix of the random effects.
X	model matrix of the fixed effects.
Z	model matrix of the random effects.

Details

EffectsEst.multiroot function performs a mamximum likelihood estimation of the fixed and random effects in a beta-binomial mixed-effects models given some initial values.

It uses the multiroot function of the rootSolve R-package.

Value

EffectsEst.multiroot returns a list of the estimates and variances of the fixed and random effects.

fixed.est	estimated value of the fixed coefficients of the regression.
random.est	estimated value of the random coefficients of the regression.
vcov.fixed	variance-covariance matrix of the estiamtion of the fixed-effects.
var.random	variance of the estimation of the random effects.
iter.fixrand	numbero of iterations in the algorithm.
conv.fixrand	convergence og the algorithm.

Author(s)

J. Najera-Zuloaga

D.-J. Lee

I. Arostegui

References

Breslow N. E. & Calyton D. G. (1993): Approximate Inference in Generalized Linear Mixed Models, Journal of the American Statistical Association, 88, 9-25.

Lee Y. & Nelder J. A. (1996): Hierarchical generalized linear models, Journal of the Royal Statistical Society. Series B, 58, 619-678.

Najera-Zuloaga J., Lee D.-J. & Arostegui I. (2018): A beta-binomial mixed-effects model approach for analysing longitudinal discrete and bounded outcomes, to appear in Biometrical Journal.

See Also

The multiroot function of the R-package rootSolve for the general Newton-Raphson algorithm.

idaejin/PROreg documentation built on May 9, 2019, 5:04 a.m.