res2table: Facility to display the results of multiple 'femlm'...
In FENmlm: Fixed Effects Nonlinear Maximum Likelihood Models

Description Usage Arguments Value Author(s) See Also Examples

View source: R/MiscFuns.R

This function aggregates the results of multiple estimations and display them in the form of only one table whose rownames are the variables and the columns contain the coefficients and standard-errors.

res2table(..., se = c("standard", "white", "cluster", "twoway", "threeway",
  "fourway"), cluster, digits = 4, pseudo = TRUE, drop, order,
  convergence = FALSE, signifCode = c(`***` = 0.01, `**` = 0.05, `*` = 0.1),
  subtitles, keepFactors = FALSE)

`...`	Used to capture different `femlm` objects. Note that any other type of element is discarded. Note that you can give a list of `femlm` objects.
`se`	Character scalar. Which kind of standard error should be prompted: “standard” (default), “White”, “cluster”, “twoway”, “threeway” or “fourway”?
`cluster`	A list of vectors. Used only if `se="cluster"`, “se=twoway”, “se=threeway” or “se=fourway”. The vectors should give the cluster of each observation. Note that if the estimation was run using `cluster`, the standard error is automatically clustered along the cluster given in `femlm`. For one-way clustering, this argument can directly be a vector (instead of a list).
`digits`	Integer. The number of digits to be displayed.
`pseudo`	Logical, default is `TRUE`. Should the pseudo R2 be displayed?
`drop`	Character vector. This element is used if some variables are not to be displayed. This should be a regular expression (see `regex` help for more info). There can be more than one regular expression. Each variable satisfying the regular expression will be discarded.
`order`	Character vector. This element is used if the user wants the variables to be ordered in a certain way. This should be a regular expression (see `regex` help for more info). There can be more than one regular expression. The variables satisfying the first regular expression will be placed first, then the order follows the sequence of regular expressions.
`convergence`	Logical, default is `TRUE`. Should the convergence state of the algorithm be displayed?
`signifCode`	Named numeric vector, used to provide the significance codes with respect to the p-value of the coefficients. Default is `c("*"=0.01, ""=0.05, "*"=0.10)`.
`subtitles`	Character vector of the same lenght as the number of models to be displayed. If provided, subtitles are added underneath the dependent variable name.
`keepFactors`	Logical, default is `FALSE`. By default, when factor variables are contained in the estimation, they are printed as if they were a cluster variable. Put to `TRUE` to display all the coefficients of the factor variables.

Returns a data.frame containing the formatted results.

Laurent Berge

See also the main estimation function femlm. Use summary.femlm to see the results with the appropriate standard-errors, getFE to extract the cluster coefficients, and the functions res2table and res2tex to visualize the results of multiple estimations.

n = 100
x = rnorm(n, 1, 5)**2
y = rnorm(n, -1, 5)**2
z = rpois(n, x*y) + rpois(n, 2)
base = data.frame(x, y, z)

# Results of the Poisson..
est_poisson = femlm(z~log(x)+log(y), base, family="poisson")
# .. and of the Negative Binomial
est_negbin = femlm(z~log(x)+log(y), base, family="negbin")

# We export the two results in one Latex table:
res2table(est_poisson, est_negbin)

# Changing the names & significance codes
res2table(est_poisson, est_negbin, dict = c("log(x)" = "First variable (ln)"),
        signifCode = c("a" = 0.001, "$$" = 0.1))