Description Usage Arguments Details Value Examples
mtable
produces a table of estimates for several models.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | 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=min(1,digits),
gs.options=NULL
)
## S3 method for class 'mtable'
relabel(x, ..., gsub = FALSE, fixed = !gsub, warn = FALSE)
## S3 method for class 'mtable'
format(x,target=c("print","LaTeX","HTML","delim"),
...
)
## S3 method for class 'mtable'
print(x,
center.at=getOption("OutDec"),
topsep="=",bottomsep="=",sectionsep="-",...)
write.mtable(object,file="",
format=c("delim","LaTeX","HTML"),...)
## S3 method for class 'mtable'
toLatex(object,...)
|
... |
as argument to |
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 |
summary.stats |
if |
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 |
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 |
float.style |
default format for floating point numbers if
no format is specified by |
.
digits |
number of significant digits if not specified by
the template returned from |
sdigits |
integer; number of digits after decimal dot for summary statistics. |
gs.options |
an optional list of arguments passed on to
|
x, object |
an object of class |
gsub, warn, fixed |
logical values, see |
target |
a character string which indicates the target format.
Currenlty the targets
"print" (see |
center.at |
a character string on which resulting values are centered.
Typically equal to ".". This is the default when |
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. |
mtable
constructs a table of estimates for regression-type models.
format.mtable
formats suitable for use with output or conversion functions
such as print.mtable
, toLatex.mtable
, or write.mtable
.
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. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | #### 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)
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)
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