mtable_format_html memisc 0.99.26.3

HTML Formatting for ‘mtable’ Results

Description

These functions formats ‘mtable’ objects into HTML format.

Usage 

mtable_format_html(x,
                    interaction.sep = NULL,
                    toprule=2,midrule=1,bottomrule=2,
                    split.dec=TRUE,
                    style=mtable_format_stdstyle,
                    margin="2ex auto",
                    sig.notes.style=c(width="inherit"),
                    ...
  )
## S4 method for signature 'memisc_mtable'
format_html(x,
                    interaction.sep = NULL,
                    toprule=2,midrule=1,bottomrule=2,
                    split.dec=TRUE,
                    style=mtable_format_stdstyle,
                    margin="2ex auto",
                    sig.notes.style=c(width="inherit"),
                    ...
  )

Arguments

x

an object of class mtable

toprule

integer; thickness in pixels of rule at the top of the table.

midrule

integer; thickness in pixels of rules within the table.

bottomrule

integer; thickness in pixels of rule at the bottom of the table.

interaction.sep

a character string that separates factors that are involved in an interaction effect or NULL. If NULL then a reasonable default is used (either a unicode character or an ampersand encoded HTML entity).

split.dec

logical; whether numbers should be centered at the decimal point by splitting the table cells.

style

string containing default the CSS styling.

margin

character string, determines the margin and thus the position of the HTML table.

sig.notes.style

a character vector with named elements, allows extra styling of the p-values notes at the bottom of the table.

...

further arguments, ignored.

Value

A character string with code suitable for inclusion into a HTML-file.

Examples 

lm0 <- lm(sr ~ pop15 + pop75,              data = LifeCycleSavings)
lm1 <- lm(sr ~                 dpi + ddpi, data = LifeCycleSavings)
lm2 <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
mtable123 <- mtable("Model 1"=lm0,"Model 2"=lm1,"Model 3"=lm2,
                   summary.stats=c("sigma","R-squared","F","p","N"))
(mtable123 <- relabel(mtable123,
                     "(Intercept)" = "Constant",
                     pop15 = "Percentage of population under 15",
                     pop75 = "Percentage of population over 75",
                     dpi = "Real per-capita disposable income",
                     ddpi = "Growth rate of real per-capita disp. income"
))

Calls:
Model 1: lm(formula = sr ~ pop15 + pop75, data = LifeCycleSavings)
Model 2: lm(formula = sr ~ dpi + ddpi, data = LifeCycleSavings)
Model 3: lm(formula = sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)

================================================================================
                                                Model 1    Model 2    Model 3
--------------------------------------------------------------------------------
  Constant                                     30.628***   6.360***  28.566***
                                               (7.409)    (1.252)    (7.355)
  Percentage of population under 15            -0.471**              -0.461**
                                               (0.147)               (0.145)
  Percentage of population over 75             -1.934                -1.691
                                               (1.041)               (1.084)
  Real per-capita disposable income                        0.001     -0.000
                                                          (0.001)    (0.001)
  Growth rate of real per-capita disp. income              0.529*     0.410*
                                                          (0.210)    (0.196)
--------------------------------------------------------------------------------
  sigma                                         3.931      4.189      3.803
  R-squared                                     0.262      0.162      0.338
  F                                             8.332      4.528      5.756
  p                                             0.001      0.016      0.001
  N                                            50         50         50
================================================================================
  Significance: *** = p < 0.001; ** = p < 0.01; * = p < 0.05

# Use HTML entity '&minus;' for minus sign
options(html.use.ampersand=TRUE)
show_html(mtable123)
Model 1 Model 2 Model 3
Constant 30 . 628*** 6 . 360*** 28 . 566***
(7 . 409) (1 . 252) (7 . 355)
Percentage of population under 15 −0 . 471** −0 . 461**
(0 . 147) (0 . 145)
Percentage of population over 75 −1 . 934 −1 . 691
(1 . 041) (1 . 084)
Real per-capita disposable income 0 . 001 −0 . 000
(0 . 001) (0 . 001)
Growth rate of real per-capita disp. income 0 . 529* 0 . 410*
(0 . 210) (0 . 196)
sigma 3 . 931 4 . 189 3 . 803
R-squared 0 . 262 0 . 162 0 . 338
F 8 . 332 4 . 528 5 . 756
p 0 . 001 0 . 016 0 . 001
N 50 50 50

Significance: *** = p < 0.001; ** = p < 0.01; * = p < 0.05

show_html(mtable123[1:2],
         sig.notes.style=c(width="30ex"))
Model 1 Model 2
Constant 30 . 628*** 6 . 360***
(7 . 409) (1 . 252)
Percentage of population under 15 −0 . 471**
(0 . 147)
Percentage of population over 75 −1 . 934
(1 . 041)
Real per-capita disposable income 0 . 001
(0 . 001)
Growth rate of real per-capita disp. income 0 . 529*
(0 . 210)
sigma 3 . 931 4 . 189
R-squared 0 . 262 0 . 162
F 8 . 332 4 . 528
p 0 . 001 0 . 016
N 50 50

Significance: *** = p < 0.001; ** = p < 0.01; * = p < 0.05

# Use unicode for minus sign (default)
options(html.use.ampersand=FALSE)
show_html(mtable123)
Model 1 Model 2 Model 3
Constant 30 . 628*** 6 . 360*** 28 . 566***
(7 . 409) (1 . 252) (7 . 355)
Percentage of population under 15 0 . 471** 0 . 461**
(0 . 147) (0 . 145)
Percentage of population over 75 1 . 934 1 . 691
(1 . 041) (1 . 084)
Real per-capita disposable income 0 . 001 0 . 000
(0 . 001) (0 . 001)
Growth rate of real per-capita disp. income 0 . 529* 0 . 410*
(0 . 210) (0 . 196)
sigma 3 . 931 4 . 189 3 . 803
R-squared 0 . 262 0 . 162 0 . 338
F 8 . 332 4 . 528 5 . 756
p 0 . 001 0 . 016 0 . 001
N 50 50 50

Significance: *** = p < 0.001; ** = p < 0.01; * = p < 0.05