glmmPQL package:MASS R Documentation _F_i_t _G_e_n_e_r_a_l_i_z_e_d _L_i_n_e_a_r _M_i_x_e_d _M_o_d_e_l_s _v_i_a _P_Q_L _D_e_s_c_r_i_p_t_i_o_n: Fit a GLMM model with multivariate normal random effects, using Penalized Quasi-Likelihood. _U_s_a_g_e: glmmPQL(fixed, random, family, data, correlation, weights, control, niter = 10, verbose = TRUE, ...) _A_r_g_u_m_e_n_t_s: fixed: a two-sided linear formula giving fixed-effects part of the model. random: a formula or list of formulae describing the random effects. family: a GLM family. data: an optional data frame used as the first place to find variables in the formulae. correlation: an optional correlation structure. weights: optional case weights as in 'glm'. control: an optional argument to be passed to 'lme'. niter: maximum number of iterations. verbose: logical: print out record of iterations? ...: Further arguments for 'lme'. _D_e_t_a_i_l_s: 'glmmPQL' works by repeated calls to 'lme', so package 'nlme' will be loaded at first use if necessary. _V_a_l_u_e: A object of class '"lme"': see 'lmeObject'. _R_e_f_e_r_e_n_c_e_s: Schall, R. (1991) Estimation in generalized linear models with random effects. _Biometrika_ *78*, 719-727. Breslow, N. E. and Clayton, D. G. (1993) Approximate inference in generalized linear mixed models. _Journal of the American Statistical Association_ *88*, 9-25. Wolfinger, R. and O'Connell, M. (1993) Generalized linear mixed models: a pseudo-likelihood approach. _Journal of Statistical Computation and Simulation_ *48*, 233-243. Venables, W. N. and Ripley, B. D. (2002) _Modern Applied Statistics with S._ Fourth edition. Springer. _S_e_e _A_l_s_o: 'lme' _E_x_a_m_p_l_e_s: library(nlme) # will be loaded automatically if omitted summary(glmmPQL(y ~ trt + I(week > 2), random = ~ 1 | ID, family = binomial, data = bacteria))