cotab_panel  R Documentation 
Panelgenerating functions visualizing contingency tables that
can be passed to cotabplot
.
cotab_mosaic(x = NULL, condvars = NULL, ...) cotab_assoc(x = NULL, condvars = NULL, ylim = NULL, ...) cotab_sieve(x = NULL, condvars = NULL, ...) cotab_loddsratio(x = NULL, condvars = NULL, ...) cotab_agreementplot(x = NULL, condvars = NULL, ...) cotab_fourfold(x = NULL, condvars = NULL, ...) cotab_coindep(x, condvars, test = c("doublemax", "maxchisq", "sumchisq"), level = NULL, n = 1000, interpolate = c(2, 4), h = NULL, c = NULL, l = NULL, lty = 1, type = c("mosaic", "assoc"), legend = FALSE, ylim = NULL, ...)
x 
a contingency tables in array form. 
condvars 
margin name(s) of the conditioning variables. 
ylim 
yaxis limits for 
test 
character indicating which type of statistic should be used for assessing conditional independence. 
level,n,h,c,l,lty,interpolate 
variables controlling the HCL shading of the
residuals, see 
type 
character indicating which type of plot should be produced. 
legend 
logical. Should a legend be produced in each panel? 
... 
further arguments passed to the plotting function (such as

These functions of class "panel_generator"
are panelgenerating
functions for use with cotabplot
, i.e., they return functions
with the interface
panel(x, condlevels)
required for cotabplot
. The functions produced by cotab_mosaic
,
cotab_assoc
and cotab_sieve
essentially only call co_table
to produce the conditioned table and then call mosaic
, assoc
or sieve
respectively with the arguments specified.
The function cotab_coindep
is similar but additionally chooses an appropriate
residualbased shading visualizing the associated conditional independence
model. The conditional independence test is carried out via coindep_test
and the shading is set up via shading_hcl
.
A description of the underlying ideas is given in Zeileis, Meyer, Hornik (2005).
Achim Zeileis Achim.Zeileis@Rproject.org
Meyer, D., Zeileis, A., and Hornik, K. (2006),
The strucplot framework: Visualizing multiway contingency tables with
vcd.
Journal of Statistical Software, 17(3), 148.
doi: 10.18637/jss.v017.i03 and available as
vignette("strucplot")
.
Zeileis, A., Meyer, D., Hornik K. (2007), Residualbased shadings for visualizing (conditional) independence, Journal of Computational and Graphical Statistics, 16, 507–525.
cotabplot
,
mosaic
,
assoc
,
sieve
,
co_table
,
coindep_test
,
shading_hcl
data("UCBAdmissions") cotabplot(~ Admit + Gender  Dept, data = UCBAdmissions) cotabplot(~ Admit + Gender  Dept, data = UCBAdmissions, panel = cotab_assoc) cotabplot(~ Admit + Gender  Dept, data = UCBAdmissions, panel = cotab_fourfold) ucb < cotab_coindep(UCBAdmissions, condvars = "Dept", type = "assoc", n = 5000, margins = c(3, 1, 1, 3)) cotabplot(~ Admit + Gender  Dept, data = UCBAdmissions, panel = ucb)
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