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memisc

mtable

Comparative Table of Model Estimates

Description

mtable produces a table of estimates for several models.

Usage

mtable(...,coef.style=getOption("coef.style"),
    summary.stats=TRUE,
    signif.symbols=getOption("signif.symbols"),
    factor.style=getOption("factor.style"),
    show.baselevel=getOption("show.baselevel"),
    baselevel.sep=getOption("baselevel.sep"),
    getSummary=eval.parent(quote(getSummary)),
    float.style=getOption("float.style"),
    digits=min(3,getOption("digits")),
    sdigits=digits,
    show.eqnames=getOption("mtable.show.eqnames",NA),
    gs.options=NULL,
    controls=NULL,
    collapse.controls=FALSE,
    control.var.indicator=getOption("control.var.indicator",c("Yes","No"))
  )
## S3 method for class 'memisc_mtable'
relabel(x, ..., gsub = FALSE, fixed = !gsub, warn = FALSE)

## S3 method for class 'memisc_mtable'
format(x,target=c("print","LaTeX","HTML","delim"),
    ...
    )

## S3 method for class 'memisc_mtable'
print(x,
    center.at=getOption("OutDec"),
    topsep="=",bottomsep="=",sectionsep="-",...)

write.mtable(object,file="",
             format=c("delim","LaTeX","HTML"),...)

## S3 method for class 'memisc_mtable'
toLatex(object,...)

Arguments

`...`	as argument to `mtable`: several model objects, e.g. of class `lm`; as argument to `print.memisc_mtable`, `toLatex.memisc_mtable`, `write.memisc_mtable`: further arguments passed to `format.memisc_mtable`; as argument to `format.memisc_mtable`: further arguments passed to `format.default`; as argument to `relabel.memisc_mtable`: further arguments passed to `dimrename`.
`coef.style`	a character string which specifies the style of coefficient values, whether standard errors, Wald/t-statistics, or significance levels are reported, etc. See `coef.style`.
`summary.stats`	if `FALSE`, no summary statistics are repored. If `TRUE` then for each object in `...` either all summary statistics are reported, or those specified by the option `"summary.stats.<cls>"`, where `<cls>` is the class of the respective object. This argument may also contain a character vector with the names of the summary statistics to report, or a list of character vectors with names of summary statistics for each object passed as argument in `...`.
`signif.symbols`	a named numeric vector to specify the "significance levels" and corresponding symbols. The numeric elements define the significance levels, the attached names define the associated symbols.
`factor.style`	a character string that specifies the style in which factor contrasts are labled. See `factor.style`.
`show.baselevel`	logical; determines whether base levels of factors are indicated for dummy coefficients
`baselevel.sep`	character that is used to separate the base level from the level that a dummy variable represents
`getSummary`	a function that computes model-related statistics that appear in the table. See `getSummary`.
`float.style`	default format for floating point numbers if no format is specified by `coef.style`

`digits`	number of significant digits if not specified by the template returned from `getCoefTemplate` `getSummaryTemplate`
`sdigits`	integer; number of digits after decimal dot for summary statistics.
`show.eqnames`	logical; if `TRUE`, left-hand sides of equations are (always) shown in the table header; if `FALSE`, left-hand sides of equations are not shown; if `NA`, left-hand sides of equations are shown only if left-hand sides differ among models or one of the models has multiple equations.
`gs.options`	an optional list of arguments passed on to `getSummary`
`controls`	an optional formula or character vector that designates "control variables" for which no coefficients are reported, but only whether they are present in the model.
`collapse.controls`	a logical values; should the report about inclusion of control variables collapsed to a single value? If yes, models should either contain none or all of the control variables.
`control.var.indicator`	a character vector with to elements; the first element being used to indicate the presence of a control variable or all control variables (if `collapse.controls=TRUE`), the second element being used otherwise. By default these elements are `"Yes"` and `"No"`.
`x, object`	an object of class `mtable`
`gsub, warn, fixed`	logical values, see `relabel`
`target`	a character string which indicates the target format. Currenlty the targets "print" (see `mtable_format_print`), "LaTeX" (see `mtable_format_latex`), "HTML" (see `mtable_format_html`), and "delim" (see `mtable_format_delim`) are supported.
`center.at`	a character string on which resulting values are centered. Typically equal to ".". This is the default when `forLaTeX==TRUE`. If `NULL`, reported values are not centered.
`topsep`	a character string that is recycled to a top rule.
`bottomsep`	a character string that is recycled to a bottom rule.
`sectionsep`	a character string that is recycled to seperate coefficients from summary statistics.
`file`	name of the file where to write to; defaults to console output.
`format`	character string that specifies the desired format.

Details

mtable constructs a table of estimates for regression-type models. format.memisc_mtable formats suitable for use with output or conversion functions such as print.memisc_mtable, toLatex.memisc_mtable, or write.memisc_mtable.

Value

A call to mtable results in an object of class "mtable" with the following components:

`coefficients`	a list that contains the model coefficients,
`summaries`	a matrix that contains the model summaries,
`calls`	a list of calls that created the model estimates being summarised.

Examples

#### Basic workflow

lm0 <- lm(sr ~ pop15 + pop75,              data = LifeCycleSavings)
lm1 <- lm(sr ~                 dpi + ddpi, data = LifeCycleSavings)
lm2 <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)

options(summary.stats.lm=c("R-squared","N"))
mtable("Model 1"=lm0,"Model 2"=lm1,"Model 3"=lm2)

options(summary.stats.lm=c("sigma","R-squared","N"))
mtable("Model 1"=lm0,"Model 2"=lm1,"Model 3"=lm2)

options(summary.stats.lm=NULL)

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"
  ))

# This produces output in tab-delimited format:
write.mtable(mtable123)

## Not run: 
# This produces output in tab-delimited format:
file123 <- "mtable123.txt"
write.mtable(mtable123,file=file123)
file.show(file123)
# The contents of this file can be pasted into Word
# and converted into a Word table.

## End(Not run)

## Not run: texfile123 <- "mtable123.tex"
write.mtable(mtable123,format="LaTeX",file=texfile123)
file.show(texfile123)
## End(Not run)

#### Examples with UC Berkeley data

berkeley <- Aggregate(Table(Admit,Freq)~.,data=UCBAdmissions)

berk0 <- glm(cbind(Admitted,Rejected)~1,data=berkeley,family="binomial")
berk1 <- glm(cbind(Admitted,Rejected)~Gender,data=berkeley,family="binomial")
berk2 <- glm(cbind(Admitted,Rejected)~Gender+Dept,data=berkeley,family="binomial")

mtable(berk0,summary.stats=c("Deviance","N"))
mtable(berk1,summary.stats=c("Deviance","N"))

mtable(berk0,berk1,berk2,summary.stats=c("Deviance","N"))

mtable(berk0,berk1,berk2,
          coef.style="horizontal",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="stat",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="ci",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="ci.se",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="ci.se.horizontal",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="ci.p.horizontal",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="ci.horizontal",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="all",
          summary.stats=c("Deviance","AIC","N"))
mtable(berk0,berk1,berk2,
          coef.style="all.nostar",
          summary.stats=c("Deviance","AIC","N"))

mtable(by(berkeley,berkeley$Dept,
  function(x)glm(cbind(Admitted,Rejected)~Gender,
        data=x,family="binomial")),
      summary.stats=c("Likelihood-ratio","N"))


mtable(By(~Gender,
  glm(cbind(Admitted,Rejected)~Dept,
        family="binomial"),
        data=berkeley),
      summary.stats=c("Likelihood-ratio","N"))

berkfull <- glm(cbind(Admitted,Rejected)~Dept/Gender - 1,
                      data=berkeley,family="binomial")
relabel(mtable(berkfull),Dept="Department",gsub=TRUE)

#### Array-like semantics

mtable123 <- mtable("Model 1"=lm0,"Model 2"=lm1,"Model 3"=lm2,
    summary.stats=c("sigma","R-squared","F","p","N"))

dim(mtable123)
dimnames(mtable123)
mtable123[c("dpi","ddpi"),
          c("Model 2","Model 3")]

#### Concatention
mt01 <- mtable(lm0,lm1,summary.stats=c("R-squared","N"))
mt12 <- mtable(lm1,lm2,summary.stats=c("R-squared","F","N"))
c(mt01,mt12) # not that this makes sense, but ...
c("Group 1"=mt01,
  "Group 2"=mt12)

memisc

Management of Survey Data and Presentation of Analysis Results

v0.99.27.3

GPL-2

Authors

Martin Elff (with contributions from Christopher N. Lawrence, Dave Atkins, Jason W. Morgan, Achim Zeileis)

Initial release

2020-11-18

mtable

Description

Usage

Arguments

Details

Value

Examples

memisc

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