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This function estimates a negative binomial regression model and calculates the corresponding incidence rate ratios.
poissonirr(formula, data, robust = FALSE, clustervar1 = NULL, clustervar2 = NULL, start = NULL, control = list())
an object of class ``formula'' (or one that can be coerced to that class).
the data frame containing these data. This argument must be used.
if TRUE the function reports White/robust standard errors.
TRUE
a character value naming the first cluster on which to adjust the standard errors.
a character value naming the second cluster on which to adjust the standard errors for two-way clustering.
starting values for the parameters in the glm model.
glm
see glm.control.
glm.control
a coefficient matrix with columns containing the estimates, associated standard errors, test statistics and p-values.
the fitted glm object.
the matched call.
If both robust=TRUE and !is.null(clustervar1) the function overrides the robust command and computes clustered standard errors.
robust=TRUE
!is.null(clustervar1)
robust
poissonmfx, glm
poissonmfx
# NOT RUN { # simulate some data set.seed(12345) n = 1000 x = rnorm(n) y = rnegbin(n, mu = exp(1 + 0.5 * x), theta = 0.5) data = data.frame(y,x) poissonirr(formula=y~x,data=data) # }
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