msm: Method of Simulated Moments

In msim: This package implements the method of simulated moments for the GLMM logit mixed model as described in Jiang's (1998) article, Consistent Estimators in Generalized Linear Mixed Models.

Description

Function to produce averaged estimates of multiple runs of method of simulated moments.

Usage

msm(family = "binomial", nsim = 1, num_MC_sims = 10000, num_subs = NULL, obs_per_sub = NULL, y.i = NULL, 
start = c(0, 1), message = TRUE, true.mu = NULL, true.sigma = NULL, method = "nleqslv")

Arguments

family	Exponential family to draw from; currently only accepts "binomial" or "poisson"
nsim	Number of simulations of MSM estimates; default is 1
num_MC_sims	Number of values used to produce one Monte Carlo estimate for MSM; default is 10000
num_subs	Index of i (number of subjects); default is NULL
obs_per_sub	Vector of length num_subs; Index of j (number of observations per subject); default is NULL
y.i	Sums over j of the y_ij, produced by simulate.fun or provided by user; default is NULL
start	Vector of starting values for (mu,sigma); default values are (0,1)
message	Logical; allows user to display message regarding standard error calculations
true.mu	True value of mu; default is NULL
true.sigma	True value of sigma; default is NULL
method	One of ("multiroot","optim","nleqslv"); default is multiroot. This determines the solver utilized within the MSM. If multiroot is selected, the function will use the multirootrootSolve function. If optim is selected, the function will use the optimbase function to minimize the Euclidean norm of the system. If nleqslv is chosen, nleqslvnleqslv will solve the system of equations using the Newton method.

Value

mu	Averages nsim estimates of mu
mu.se	Averages nsim estimates of root mean squared error mu
sigma	Averages nsim estimates of sigma
sigma.se	Averages nsim estimates of root mean squared error sigma
sigma2	Averages nsim estimates of sigma2 based on squaring the estimate of sigma
sigma2.se	Averages nsim estimates of root mean squared error sigma2

Author(s)

Lindsey Dietz

References

Jiang, J. (1998). Consistent Estimators in Generalized Linear Mixed Models. Journal of the American Statistical Association, 93, 720–729.

Jiang, J. and Zhang, W. (2001). Robust estimation in generalized linear mixed models. Biometrika, 88, 753–765.

See Also

optim multiroot nleqslv

msim documentation built on May 2, 2019, 5:50 p.m.