var.grp
)
of var.cnt
and prints the result as HTML table.
sjt.grpmean(var.cnt, var.grp, weight.by = NULL, value.labels = NULL, digits = 2, digits.summary = 3, CSS = NULL, encoding = NULL, file = NULL, use.viewer = TRUE, no.output = FALSE, remove.spaces = TRUE)
var.cnt
is grouped into the categories represented by var.grp
.NULL
, so no weights are used.list
of character vectors)
with value labels of the supplied variables, which will be used
to label variable values in the output.list
-object with user-defined style-sheet-definitions, according to the
official CSS syntax. See 'Details'.NULL
, so encoding will be auto-detected
depending on your platform (e.g., "UTF-8"
for Unix and "Windows-1252"
for
Windows OS). Change encoding if specific chars are not properly displayed (e.g. German umlauts).NULL
(default), the output will be saved as temporary file and
openend either in the IDE's viewer pane or the default web browser.TRUE
, the HTML table is shown in the IDE's viewer pane. If
FALSE
or no viewer available, the HTML table is opened in a web browser.TRUE
, the html-output is neither opened in a browser nor shown in
the viewer pane and not even saved to file. This option is useful when the html output
should be used in knitr
documents. The html output can be accessed via the return
value.TRUE
, leading spaces are removed from all lines in the final string
that contains the html-data. Use this, if you want to remove parantheses for html-tags. The html-source
may look less pretty, but it may help when exporting html-tables to office tools.list
with
df
),
page.style
),
page.content
),
output.complete
) and
knitr
)
var.cnt
as dependent
and var.grp
as independent variable, by calling
lm(var.cnt ~ as.factor(var.grp))
, to get p-values for each
sub-group and the complete "model". Thus, p-values indicate whether
each group-mean is significantly different from the reference
group (reference level of var.grp
). Statistics like mean values are
based on subsetted groups (i.e. var.cnt
is divided into sub-groups
indicated by var.grp
).
Furthermore, see 'Details' in sjt.frq
.
sjp.aov1
## Not run:
# library(sjmisc)
# data(efc)
# sjt.grpmean(efc$c12hour, efc$e42dep)## End(Not run)
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