install.packages("multilevel", repos="http://lib.stat.cmu.edu/R/CRAN")

Tools for making Latex tables in R

http://stackoverflow.com/questions/5465314/tools-for-making-latex-tables-in-r

GLMER Latex

1. http://cran.r-project.org/web/packages/memisc/memisc.pdf

· mtable()

· toLatex()

2. http://hlplab.wordpress.com/2010/06/15/r-code-for-latex-tables-of-lmer-model-effects/

3. https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q1/005564.html

Tables adapted from “Applied Econometrics with R” by Kleiber and Zeileis.

Table 3.1:  Generic  functions for fitted (linear) model objects.

Function	Description
print()	simple printed display
summary()	standard regression  output
coef()	(or coefficients()) extracting the regression  coefficients
residuals()	(or resid())  extracting residuals
fitted()	(or fitted.values()) extracting fitted values
anova()	comparison of nested  models (see 11.24 “R Cookbook” for example); see p. 65 Kleiber for linear.hypothesis(); finally, see p. 69 Kleiber for anova() example.
predict()	predictions for new data
plot()	diagnostic plots
confint()	confidence  intervals for the regression  coefficients
deviance()	residual sum of squares
vcov()	(estimated) variance-covariance matrix
logLik()	log-likelihood  (assuming normally distributed errors)
AIC()	information  criteria  including   AIC,  BIC/SBC  (assuming normally distributed errors)

Table 2.1:  A selective list of arguments to par().

Argument	Description
axes	should  axes be drawn?
bg	background color
cex	size of a point or symbol
col	color
las	orientation of axis labels
lty, lwd	line type and  line width
main, sub	title and  subtitle
mar	size of margins
mfcol, mfrow	array  defining  layout for several  graphs  on a plot
pch	plotting symbol
type	types (see text)
xlab, ylab	axis labels
xlim, ylim	axis ranges
xlog, ylog, log	logarithmic scales

Table 3.2:  Specification of interactions in formulas.

Formula	Description
y ~ a + x	Model  without  interaction:  identical  slopes  with  respect to x but different intercepts with respect to a.
y ~ a * x y ~ a + x + a:x	Model with interaction: the term a:x gives the difference in slopes compared with the reference  category.
y ~ a / x y ~ a + x %in% a	Model with interaction: produces the same fitted values  as the model above but using a nested  coefficient coding.  An explicit slope estimate is computed for each category in a [Kleiber]. Terms of the form a/x, where a is a factor, are best thought of as “separate regression models of type 1 + x within the levels of a.” [Venables].
y ~ (a + b + c)^2 y ~ a*b*c - a:b:c	Model with all two-way interactions (excluding the three- way interaction).

Table 5.2:  Further packages  for microeconometrics.

Package	Description
gam	Generalized additive models  (Hastie 2006)
lme4	Nonlinear random-effects  models:  counts,  binary  depen- dent variables, etc.  (Bates 2008)
mgcv	Generalized additive (mixed) models  (Wood  2006)
micEcon	Demand systems, cost  and  production  functions  (Henningsen  2008)
mlogit	Multinomial  logit  models  with  choice-specific  variables (Croissant 2008)
robustbase	Robust/resistant regression  for  GLMs (Maechler, Rousseeuw,   Croux,   Todorov,  Ruckstuhl,  and  Salibian-  Barrera 2007)
sampleSelection	Selection  models:  generalized tobit, heckit  (Toomet  and Henningsen 2008)