memisc (version 0.99.22)

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
  )
# S3 method for memisc_mtable
relabel(x, …, gsub = FALSE, fixed = !gsub, warn = FALSE)
# S3 method for memisc_mtable
format(x,target=c("print","LaTeX","HTML","delim"),
    …
    )
# S3 method for memisc_mtable
print(x,
    center.at=getOption("OutDec"),
    topsep="=",bottomsep="=",sectionsep="-",…)
write.mtable(object,file="",
             format=c("delim","LaTeX","HTML"),…)
# S3 method for 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

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.

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.

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.

Examples

# NOT RUN {
#### 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.
# }
# NOT RUN {
texfile123 <- "mtable123.tex"
write.mtable(mtable123,format="LaTeX",file=texfile123)
file.show(texfile123)
# }
# 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)
# }