Last updated on 2026-03-10 21:54:03 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| kutils | 2 | 12 | |
| rockchalk | 8 | 6 |
Current CRAN status: NOTE: 2, OK: 12
Version: 1.73
Check: dependencies in R code
Result: NOTE
Namespace in Imports field not imported from: ‘RUnit’
All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Current CRAN status: ERROR: 8, NOTE: 6
Version: 1.8.157
Check: Rd files
Result: NOTE
checkRd: (-1) descriptiveTable.Rd:18: Lost braces
18 | other object type that does not fail in code{model.frame(object)}.}
| ^
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-macos-arm64, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.8.157
Check: examples
Result: ERROR
Running examples in ‘rockchalk-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: outreg
> ### Title: Creates a publication quality result table for regression
> ### models. Works with models fitted with lm, glm, as well as lme4.
> ### Aliases: outreg
> ### Keywords: regression
>
> ### ** Examples
>
> set.seed(2134234)
> dat <- data.frame(x1 = rnorm(100), x2 = rnorm(100))
> dat$y1 <- 30 + 5 * rnorm(100) + 3 * dat$x1 + 4 * dat$x2
> dat$y2 <- rnorm(100) + 5 * dat$x2
> m1 <- lm(y1 ~ x1, data = dat)
> m2 <- lm(y1 ~ x2, data = dat)
> m3 <- lm(y1 ~ x1 + x2, data = dat)
> gm1 <- glm(y1 ~ x1, family = Gamma, data = dat)
> outreg(m1, title = "My One Tightly Printed Regression", float = TRUE)
\begin{table}
\caption{My One Tightly Printed Regression}\label{regrlabl}
\begin{tabular}{@{}l*{2}{l}@{}}
\hline
&\multicolumn{1}{l}{M1 }\tabularnewline
&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** \tabularnewline
&(0.618)\tabularnewline
x1 & 1.546* \tabularnewline
&(0.692)\tabularnewline
\hline
N&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121\tabularnewline
$R^2$&0.048\tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ex1 <- outreg(m1, title = "My One Tightly Printed Regression",
+ float = TRUE, print.results = FALSE, centering = "siunitx")
> ## Show markup, Save to file with cat()
> cat(ex1)
\begin{table}
\caption{My One Tightly Printed Regression}\label{regrlabl}
\begin{tabular}{@{}l*{1}{S[
input-symbols = ( ),
group-digits = false,
table-number-alignment = center,
%table-space-text-pre = (,
table-align-text-pre = false,
table-align-text-post = false,
table-space-text-post = {***},
parse-units = false]}@{}}
\hline
&\multicolumn{1}{c}{M1 }\tabularnewline
&\multicolumn{1}{c}{Estimate}\tabularnewline
&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** \tabularnewline
&(0.618)\tabularnewline
x1 & 1.546* \tabularnewline
&(0.692)\tabularnewline
\hline
N&\multicolumn{1}{c}{100} \tabularnewline
RMSE&6.121\tabularnewline
$R^2$&0.048\tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ## cat(ex1, file = "ex1.tex")
>
> ex2 <- outreg(list("Fingers" = m1), tight = FALSE,
+ title = "My Only Spread Out Regressions", float = TRUE,
+ alpha = c(0.05, 0.01, 0.001))
\begin{table}
\caption{My Only Spread Out Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{2}{l}{Fingers }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & (0.618) \tabularnewline
x1 & 1.546* & (0.692) \tabularnewline
\hline
N&\multicolumn{1}{l}{100} & \tabularnewline
RMSE&6.121\tabularnewline
$R^2$&0.048\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex3 <- outreg(list("Model A" = m1, "Model B label with Spaces" = m2),
+ varLabels = list(x1 = "Billie"),
+ title = "My Two Linear Regressions", request = c(fstatistic = "F"),
+ print.results = TRUE)
\begin{table}
\caption{My Two Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B label with Spaces }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\multicolumn{1}{c}{44.4(1,98)***}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex3)
\begin{table}
\caption{My Two Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B label with Spaces }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\multicolumn{1}{c}{44.4(1,98)***}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex4 <- outreg(list("Model A" = m1, "Model B" = m2),
+ modelLabels = c("Overrides ModelA", "Overrides ModelB"),
+ varLabels = list(x1 = "Billie"),
+ title = "Note modelLabels Overrides model names")
\begin{table}
\caption{Note modelLabels Overrides model names}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Overrides ModelA } &\multicolumn{1}{l}{Overrides ModelB }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex4)
\begin{table}
\caption{Note modelLabels Overrides model names}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Overrides ModelA } &\multicolumn{1}{l}{Overrides ModelB }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ##'
> ex5 <- outreg(list("Whichever" = m1, "Whatever" = m2),
+ title = "Still have showAIC argument, as in previous versions",
+ showAIC = TRUE, float = TRUE, centering = "siunitx")
\begin{table}
\caption{Still have showAIC argument, as in previous versions}\label{regrlabl}
\begin{tabular}{@{}l*{2}{S[
input-symbols = ( ),
group-digits = false,
table-number-alignment = center,
%table-space-text-pre = (,
table-align-text-pre = false,
table-align-text-post = false,
table-space-text-post = {***},
parse-units = false]}@{}}
\hline
&\multicolumn{1}{c}{Whichever } &\multicolumn{1}{c}{Whatever }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{Estimate}\tabularnewline
&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
x1 & 1.546* &\multicolumn{1}{c}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{c}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{c}{100}&\multicolumn{1}{c}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
AIC&650.109 &617.694\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex5s <- outreg(list("Whichever" = m1, "Whatever" = m2),
+ title = "Still have showAIC argument, as in previous versions",
+ showAIC = TRUE, float = TRUE, centering = "siunitx")
\begin{table}
\caption{Still have showAIC argument, as in previous versions}\label{regrlabl}
\begin{tabular}{@{}l*{2}{S[
input-symbols = ( ),
group-digits = false,
table-number-alignment = center,
%table-space-text-pre = (,
table-align-text-pre = false,
table-align-text-post = false,
table-space-text-post = {***},
parse-units = false]}@{}}
\hline
&\multicolumn{1}{c}{Whichever } &\multicolumn{1}{c}{Whatever }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{Estimate}\tabularnewline
&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
x1 & 1.546* &\multicolumn{1}{c}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{c}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{c}{100}&\multicolumn{1}{c}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
AIC&650.109 &617.694\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
>
> ex6 <- outreg(list("Whatever" = m1, "Whatever" =m2),
+ title = "Another way to get AIC output",
+ runFuns = c("AIC" = "Akaike IC"))
\begin{table}
\caption{Another way to get AIC output}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Whatever } &\multicolumn{1}{l}{Whatever }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 30.245*** \tabularnewline
&(0.618)&(0.618)\tabularnewline
x1 & 1.546* & 1.546* \tabularnewline
&(0.692)&(0.692)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }&\multicolumn{1}{l}{\_ }\tabularnewline
& &\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
Akaike IC&\multicolumn{1}{c}{650.11} &\multicolumn{1}{c}{617.69}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex6)
\begin{table}
\caption{Another way to get AIC output}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Whatever } &\multicolumn{1}{l}{Whatever }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 30.245*** \tabularnewline
&(0.618)&(0.618)\tabularnewline
x1 & 1.546* & 1.546* \tabularnewline
&(0.692)&(0.692)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }&\multicolumn{1}{l}{\_ }\tabularnewline
& &\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
Akaike IC&\multicolumn{1}{c}{650.11} &\multicolumn{1}{c}{617.69}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex7 <- outreg(list("Amod" = m1, "Bmod" = m2, "Gmod" = m3),
+ title = "My Three Linear Regressions", float = FALSE)
\begin{table}
\caption{My Three Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{4}{l}@{}}
\hline
&\multicolumn{1}{l}{Amod } &\multicolumn{1}{l}{Bmod } &\multicolumn{1}{l}{Gmod }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** \tabularnewline
&(0.692) &&(0.555)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397\tabularnewline
\hline
\hline
\multicolumn{4}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex7)
\begin{table}
\caption{My Three Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{4}{l}@{}}
\hline
&\multicolumn{1}{l}{Amod } &\multicolumn{1}{l}{Bmod } &\multicolumn{1}{l}{Gmod }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** \tabularnewline
&(0.692) &&(0.555)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397\tabularnewline
\hline
\hline
\multicolumn{4}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ## A new feature in 1.85 is ability to provide vectors of beta estimates
> ## standard errors, and p values if desired.
> ## Suppose you have robust standard errors!
> if (require(car)){
+ newSE <- sqrt(diag(car::hccm(m3)))
+ ex8 <- outreg(list("Model A" = m1, "Model B" = m2, "Model C" = m3, "Model C w Robust SE" = m3),
+ SElist= list("Model C w Robust SE" = newSE))
+ cat(ex8)
+ }
Loading required package: car
Loading required package: carData
\begin{tabular}{@{}l*{5}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B } &\multicolumn{1}{l}{Model C } &\multicolumn{1}{l}{Model C w Robust SE }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)&(0.481)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** & 2.217*** \tabularnewline
&(0.692) &&(0.555)&(0.618)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)&(0.464)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397 &0.397\tabularnewline
\hline
\hline
\multicolumn{5}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\begin{tabular}{@{}l*{5}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B } &\multicolumn{1}{l}{Model C } &\multicolumn{1}{l}{Model C w Robust SE }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)&(0.481)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** & 2.217*** \tabularnewline
&(0.692) &&(0.555)&(0.618)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)&(0.464)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397 &0.397\tabularnewline
\hline
\hline
\multicolumn{5}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
>
> ex11 <- outreg(list("I Love Long Titles" = m1,
+ "Prefer Brevity" = m2,
+ "Short" = m3), tight = FALSE, float = FALSE)
\begin{tabular}{@{}l*{7}{l}@{}}
\hline
&\multicolumn{2}{l}{I Love Long Titles } &\multicolumn{2}{l}{Prefer Brevity } &\multicolumn{2}{l}{Short }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & (0.618) & 29.774*** & (0.522) & 30.013*** & (0.490) \tabularnewline
x1 & 1.546* & (0.692) &\multicolumn{1}{l}{\_ }&& 2.217*** & (0.555) \tabularnewline
x2 &\multicolumn{1}{l}{\_ }&& 3.413*** & (0.512) & 3.717*** & (0.483) \tabularnewline
\hline
N&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} & \tabularnewline
RMSE&6.121&&5.205&&4.849\tabularnewline
$R^2$&0.048&&0.312&&0.409\tabularnewline
adj $R^2$&0.039&&0.305&&0.397\tabularnewline
\hline
\hline
\multicolumn{7}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
> cat(ex11)
\begin{tabular}{@{}l*{7}{l}@{}}
\hline
&\multicolumn{2}{l}{I Love Long Titles } &\multicolumn{2}{l}{Prefer Brevity } &\multicolumn{2}{l}{Short }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & (0.618) & 29.774*** & (0.522) & 30.013*** & (0.490) \tabularnewline
x1 & 1.546* & (0.692) &\multicolumn{1}{l}{\_ }&& 2.217*** & (0.555) \tabularnewline
x2 &\multicolumn{1}{l}{\_ }&& 3.413*** & (0.512) & 3.717*** & (0.483) \tabularnewline
\hline
N&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} & \tabularnewline
RMSE&6.121&&5.205&&4.849\tabularnewline
$R^2$&0.048&&0.312&&0.409\tabularnewline
adj $R^2$&0.039&&0.305&&0.397\tabularnewline
\hline
\hline
\multicolumn{7}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
> ##'
> ex12 <- outreg(list("GLM" = gm1), float = TRUE)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{2}{l}@{}}
\hline
&\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 0.033*** \tabularnewline
&(0.001)\tabularnewline
x1 & -0.002* \tabularnewline
&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100} \tabularnewline
RMSE&\tabularnewline
$R^2$&\tabularnewline
Deviance&4.301\tabularnewline
$-2LLR (Model \chi^2)$ & 0.208 \tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex12)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{2}{l}@{}}
\hline
&\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 0.033*** \tabularnewline
&(0.001)\tabularnewline
x1 & -0.002* \tabularnewline
&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100} \tabularnewline
RMSE&\tabularnewline
$R^2$&\tabularnewline
Deviance&4.301\tabularnewline
$-2LLR (Model \chi^2)$ & 0.208 \tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex13 <- outreg(list("OLS" = m1, "GLM" = gm1), float = TRUE,
+ alpha = c(0.05, 0.01))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245** & 0.033** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex13)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245** & 0.033** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$}\tabularnewline
\end{tabular}
\end{table}
> ##'
> ex14 <- outreg(list(OLS = m1, GLM = gm1), float = TRUE,
+ request = c(fstatistic = "F"), runFuns = c("BIC" = "BIC"))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 0.033*** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{659.82}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex14)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 0.033*** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{659.82}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ex15 <- outreg(list(OLS = m1, GLM = gm1), float = TRUE,
+ request = c(fstatistic = "F"), runFuns = c("BIC" = "BIC"),
+ digits = 5, alpha = c(0.01))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.24550* & 0.03313* \tabularnewline
&(0.61763)&(0.00068)\tabularnewline
x1 & 1.54553 & -0.00173 \tabularnewline
&(0.69242)&(0.00078)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.12090 &\tabularnewline
$R^2$&0.04838 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.9821(1,98)} &\tabularnewline
Deviance& &4.30066\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.20827 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{659.82}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.01$}\tabularnewline
\end{tabular}
\end{table}
>
> ex16 <- outreg(list("OLS 1" = m1, "OLS 2" = m2, GLM = gm1), float = TRUE,
+ request = c(fstatistic = "F"),
+ runFuns = c("BIC" = "BIC", logLik = "ll"),
+ digits = 5, alpha = c(0.05, 0.01, 0.001))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{4}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS 1 } &\multicolumn{1}{l}{OLS 2 } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.24550*** & 29.77420*** & 0.03313*** \tabularnewline
&(0.61763)&(0.52229)&(0.00068)\tabularnewline
x1 & 1.54553* &\multicolumn{1}{l}{\_ }& -0.00173* \tabularnewline
&(0.69242) &&(0.00078)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.41342*** &\multicolumn{1}{l}{\_ }\tabularnewline
&&(0.51222) &\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.12090 &5.20508 &\tabularnewline
$R^2$&0.04838 &0.31184 &\tabularnewline
adj $R^2$&0.03867 &0.30482 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.9821(1,98)*} &\multicolumn{1}{c}{44.409(1,98)***} &\tabularnewline
Deviance& & &4.30066\tabularnewline
$-2LLR (Model \chi^2)$ & & & 0.20827 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{625.51} &\multicolumn{1}{c}{659.82}\tabularnewline
ll&\multicolumn{1}{c}{-322.05(3)} &\multicolumn{1}{c}{-305.85(3)} &\multicolumn{1}{c}{-323(3)}\tabularnewline
\hline
\hline
\multicolumn{4}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex17 <- outreg(list("Model A" = gm1, "Model B label with Spaces" = m2),
+ request = c(fstatistic = "F"),
+ runFuns = c("BIC" = "Schwarz IC", "AIC" = "Akaike IC",
+ "nobs" = "N Again?"))
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B label with Spaces }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 0.033*** & 29.774*** \tabularnewline
&(0.001)&(0.522)\tabularnewline
x1 & -0.002* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.001) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE& &5.205\tabularnewline
$R^2$& &0.312\tabularnewline
adj $R^2$& &0.305\tabularnewline
F($df_{num}$,$df_{denom}$)& &\multicolumn{1}{c}{44.4(1,98)***}\tabularnewline
Deviance&4.301 &\tabularnewline
$-2LLR (Model \chi^2)$ & 0.208 & \tabularnewline
Schwarz IC&\multicolumn{1}{c}{659.82} &\multicolumn{1}{c}{625.51}\tabularnewline
Akaike IC&\multicolumn{1}{c}{652.00} &\multicolumn{1}{c}{617.69}\tabularnewline
N Again?&\multicolumn{1}{c}{100} &\multicolumn{1}{c}{100}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
>
> ## Here's a fit example from lme4.
> if (require(lme4) && require(car)){
+ fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
+ ex18 <- outreg(fm1)
+ cat(ex18)
+ ## Fit same with lm for comparison
+ lm1 <- lm(Reaction ~ Days, sleepstudy)
+ ## Get robust standard errors
+ lm1rse <- sqrt(diag(car::hccm(lm1)))
+
+ if(interactive()){
+ ex19 <- outreg(list("Random Effects" = fm1,
+ "OLS" = lm1, "OLS Robust SE" = lm1),
+ SElist = list("OLS Robust SE" = lm1rse), type = "html")
+ }
+ ## From the glmer examples
+ gm2 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
+ data = cbpp, family = binomial)
+ lm2 <- lm(incidence/size ~ period, data = cbpp)
+ lm2rse <- sqrt(diag(car::hccm(lm2)))
+ ## Lets see what MASS::rlm objects do? Mostly OK
+ rlm2 <- MASS::rlm(incidence/size ~ period, data = cbpp)
+
+ }
Loading required package: lme4
Loading required package: Matrix
Error in get(x, envir = ns, inherits = FALSE) :
object 'formatVC' not found
Calls: outreg ... getVCmat -> lapply -> FUN -> getFromNamespace -> get
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-release-linux-x86_64
Version: 1.8.157
Check: examples
Result: ERROR
Running examples in ‘rockchalk-Ex.R’ failed
The error most likely occurred in:
> ### Name: outreg
> ### Title: Creates a publication quality result table for regression
> ### models. Works with models fitted with lm, glm, as well as lme4.
> ### Aliases: outreg
> ### Keywords: regression
>
> ### ** Examples
>
> set.seed(2134234)
> dat <- data.frame(x1 = rnorm(100), x2 = rnorm(100))
> dat$y1 <- 30 + 5 * rnorm(100) + 3 * dat$x1 + 4 * dat$x2
> dat$y2 <- rnorm(100) + 5 * dat$x2
> m1 <- lm(y1 ~ x1, data = dat)
> m2 <- lm(y1 ~ x2, data = dat)
> m3 <- lm(y1 ~ x1 + x2, data = dat)
> gm1 <- glm(y1 ~ x1, family = Gamma, data = dat)
> outreg(m1, title = "My One Tightly Printed Regression", float = TRUE)
\begin{table}
\caption{My One Tightly Printed Regression}\label{regrlabl}
\begin{tabular}{@{}l*{2}{l}@{}}
\hline
&\multicolumn{1}{l}{M1 }\tabularnewline
&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** \tabularnewline
&(0.618)\tabularnewline
x1 & 1.546* \tabularnewline
&(0.692)\tabularnewline
\hline
N&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121\tabularnewline
$R^2$&0.048\tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ex1 <- outreg(m1, title = "My One Tightly Printed Regression",
+ float = TRUE, print.results = FALSE, centering = "siunitx")
> ## Show markup, Save to file with cat()
> cat(ex1)
\begin{table}
\caption{My One Tightly Printed Regression}\label{regrlabl}
\begin{tabular}{@{}l*{1}{S[
input-symbols = ( ),
group-digits = false,
table-number-alignment = center,
%table-space-text-pre = (,
table-align-text-pre = false,
table-align-text-post = false,
table-space-text-post = {***},
parse-units = false]}@{}}
\hline
&\multicolumn{1}{c}{M1 }\tabularnewline
&\multicolumn{1}{c}{Estimate}\tabularnewline
&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** \tabularnewline
&(0.618)\tabularnewline
x1 & 1.546* \tabularnewline
&(0.692)\tabularnewline
\hline
N&\multicolumn{1}{c}{100} \tabularnewline
RMSE&6.121\tabularnewline
$R^2$&0.048\tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ## cat(ex1, file = "ex1.tex")
>
> ex2 <- outreg(list("Fingers" = m1), tight = FALSE,
+ title = "My Only Spread Out Regressions", float = TRUE,
+ alpha = c(0.05, 0.01, 0.001))
\begin{table}
\caption{My Only Spread Out Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{2}{l}{Fingers }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & (0.618) \tabularnewline
x1 & 1.546* & (0.692) \tabularnewline
\hline
N&\multicolumn{1}{l}{100} & \tabularnewline
RMSE&6.121\tabularnewline
$R^2$&0.048\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex3 <- outreg(list("Model A" = m1, "Model B label with Spaces" = m2),
+ varLabels = list(x1 = "Billie"),
+ title = "My Two Linear Regressions", request = c(fstatistic = "F"),
+ print.results = TRUE)
\begin{table}
\caption{My Two Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B label with Spaces }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\multicolumn{1}{c}{44.4(1,98)***}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex3)
\begin{table}
\caption{My Two Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B label with Spaces }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\multicolumn{1}{c}{44.4(1,98)***}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex4 <- outreg(list("Model A" = m1, "Model B" = m2),
+ modelLabels = c("Overrides ModelA", "Overrides ModelB"),
+ varLabels = list(x1 = "Billie"),
+ title = "Note modelLabels Overrides model names")
\begin{table}
\caption{Note modelLabels Overrides model names}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Overrides ModelA } &\multicolumn{1}{l}{Overrides ModelB }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex4)
\begin{table}
\caption{Note modelLabels Overrides model names}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Overrides ModelA } &\multicolumn{1}{l}{Overrides ModelB }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
Billie & 1.546* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ##'
> ex5 <- outreg(list("Whichever" = m1, "Whatever" = m2),
+ title = "Still have showAIC argument, as in previous versions",
+ showAIC = TRUE, float = TRUE, centering = "siunitx")
\begin{table}
\caption{Still have showAIC argument, as in previous versions}\label{regrlabl}
\begin{tabular}{@{}l*{2}{S[
input-symbols = ( ),
group-digits = false,
table-number-alignment = center,
%table-space-text-pre = (,
table-align-text-pre = false,
table-align-text-post = false,
table-space-text-post = {***},
parse-units = false]}@{}}
\hline
&\multicolumn{1}{c}{Whichever } &\multicolumn{1}{c}{Whatever }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{Estimate}\tabularnewline
&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
x1 & 1.546* &\multicolumn{1}{c}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{c}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{c}{100}&\multicolumn{1}{c}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
AIC&650.109 &617.694\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex5s <- outreg(list("Whichever" = m1, "Whatever" = m2),
+ title = "Still have showAIC argument, as in previous versions",
+ showAIC = TRUE, float = TRUE, centering = "siunitx")
\begin{table}
\caption{Still have showAIC argument, as in previous versions}\label{regrlabl}
\begin{tabular}{@{}l*{2}{S[
input-symbols = ( ),
group-digits = false,
table-number-alignment = center,
%table-space-text-pre = (,
table-align-text-pre = false,
table-align-text-post = false,
table-space-text-post = {***},
parse-units = false]}@{}}
\hline
&\multicolumn{1}{c}{Whichever } &\multicolumn{1}{c}{Whatever }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{Estimate}\tabularnewline
&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** \tabularnewline
&(0.618)&(0.522)\tabularnewline
x1 & 1.546* &\multicolumn{1}{c}{\_ }\tabularnewline
&(0.692) &\tabularnewline
x2 &\multicolumn{1}{c}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{c}{100}&\multicolumn{1}{c}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
AIC&650.109 &617.694\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
>
> ex6 <- outreg(list("Whatever" = m1, "Whatever" =m2),
+ title = "Another way to get AIC output",
+ runFuns = c("AIC" = "Akaike IC"))
\begin{table}
\caption{Another way to get AIC output}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Whatever } &\multicolumn{1}{l}{Whatever }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 30.245*** \tabularnewline
&(0.618)&(0.618)\tabularnewline
x1 & 1.546* & 1.546* \tabularnewline
&(0.692)&(0.692)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }&\multicolumn{1}{l}{\_ }\tabularnewline
& &\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
Akaike IC&\multicolumn{1}{c}{650.11} &\multicolumn{1}{c}{617.69}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex6)
\begin{table}
\caption{Another way to get AIC output}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Whatever } &\multicolumn{1}{l}{Whatever }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 30.245*** \tabularnewline
&(0.618)&(0.618)\tabularnewline
x1 & 1.546* & 1.546* \tabularnewline
&(0.692)&(0.692)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }&\multicolumn{1}{l}{\_ }\tabularnewline
& &\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205\tabularnewline
$R^2$&0.048 &0.312\tabularnewline
adj $R^2$&0.039 &0.305\tabularnewline
Akaike IC&\multicolumn{1}{c}{650.11} &\multicolumn{1}{c}{617.69}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex7 <- outreg(list("Amod" = m1, "Bmod" = m2, "Gmod" = m3),
+ title = "My Three Linear Regressions", float = FALSE)
\begin{table}
\caption{My Three Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{4}{l}@{}}
\hline
&\multicolumn{1}{l}{Amod } &\multicolumn{1}{l}{Bmod } &\multicolumn{1}{l}{Gmod }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** \tabularnewline
&(0.692) &&(0.555)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397\tabularnewline
\hline
\hline
\multicolumn{4}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex7)
\begin{table}
\caption{My Three Linear Regressions}\label{regrlabl}
\begin{tabular}{@{}l*{4}{l}@{}}
\hline
&\multicolumn{1}{l}{Amod } &\multicolumn{1}{l}{Bmod } &\multicolumn{1}{l}{Gmod }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** \tabularnewline
&(0.692) &&(0.555)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397\tabularnewline
\hline
\hline
\multicolumn{4}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ## A new feature in 1.85 is ability to provide vectors of beta estimates
> ## standard errors, and p values if desired.
> ## Suppose you have robust standard errors!
> if (require(car)){
+ newSE <- sqrt(diag(car::hccm(m3)))
+ ex8 <- outreg(list("Model A" = m1, "Model B" = m2, "Model C" = m3, "Model C w Robust SE" = m3),
+ SElist= list("Model C w Robust SE" = newSE))
+ cat(ex8)
+ }
Loading required package: car
Loading required package: carData
\begin{tabular}{@{}l*{5}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B } &\multicolumn{1}{l}{Model C } &\multicolumn{1}{l}{Model C w Robust SE }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)&(0.481)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** & 2.217*** \tabularnewline
&(0.692) &&(0.555)&(0.618)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)&(0.464)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397 &0.397\tabularnewline
\hline
\hline
\multicolumn{5}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\begin{tabular}{@{}l*{5}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B } &\multicolumn{1}{l}{Model C } &\multicolumn{1}{l}{Model C w Robust SE }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 29.774*** & 30.013*** & 30.013*** \tabularnewline
&(0.618)&(0.522)&(0.490)&(0.481)\tabularnewline
x1 & 1.546* &\multicolumn{1}{l}{\_ }& 2.217*** & 2.217*** \tabularnewline
&(0.692) &&(0.555)&(0.618)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** & 3.717*** & 3.717*** \tabularnewline
&&(0.512)&(0.483)&(0.464)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &5.205 &4.849 &4.849\tabularnewline
$R^2$&0.048 &0.312 &0.409 &0.409\tabularnewline
adj $R^2$&0.039 &0.305 &0.397 &0.397\tabularnewline
\hline
\hline
\multicolumn{5}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
>
> ex11 <- outreg(list("I Love Long Titles" = m1,
+ "Prefer Brevity" = m2,
+ "Short" = m3), tight = FALSE, float = FALSE)
\begin{tabular}{@{}l*{7}{l}@{}}
\hline
&\multicolumn{2}{l}{I Love Long Titles } &\multicolumn{2}{l}{Prefer Brevity } &\multicolumn{2}{l}{Short }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & (0.618) & 29.774*** & (0.522) & 30.013*** & (0.490) \tabularnewline
x1 & 1.546* & (0.692) &\multicolumn{1}{l}{\_ }&& 2.217*** & (0.555) \tabularnewline
x2 &\multicolumn{1}{l}{\_ }&& 3.413*** & (0.512) & 3.717*** & (0.483) \tabularnewline
\hline
N&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} & \tabularnewline
RMSE&6.121&&5.205&&4.849\tabularnewline
$R^2$&0.048&&0.312&&0.409\tabularnewline
adj $R^2$&0.039&&0.305&&0.397\tabularnewline
\hline
\hline
\multicolumn{7}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
> cat(ex11)
\begin{tabular}{@{}l*{7}{l}@{}}
\hline
&\multicolumn{2}{l}{I Love Long Titles } &\multicolumn{2}{l}{Prefer Brevity } &\multicolumn{2}{l}{Short }\tabularnewline
&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}&\multicolumn{1}{c}{Estimate}&\multicolumn{1}{c}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & (0.618) & 29.774*** & (0.522) & 30.013*** & (0.490) \tabularnewline
x1 & 1.546* & (0.692) &\multicolumn{1}{l}{\_ }&& 2.217*** & (0.555) \tabularnewline
x2 &\multicolumn{1}{l}{\_ }&& 3.413*** & (0.512) & 3.717*** & (0.483) \tabularnewline
\hline
N&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} &&\multicolumn{1}{l}{100} & \tabularnewline
RMSE&6.121&&5.205&&4.849\tabularnewline
$R^2$&0.048&&0.312&&0.409\tabularnewline
adj $R^2$&0.039&&0.305&&0.397\tabularnewline
\hline
\hline
\multicolumn{7}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
> ##'
> ex12 <- outreg(list("GLM" = gm1), float = TRUE)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{2}{l}@{}}
\hline
&\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 0.033*** \tabularnewline
&(0.001)\tabularnewline
x1 & -0.002* \tabularnewline
&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100} \tabularnewline
RMSE&\tabularnewline
$R^2$&\tabularnewline
Deviance&4.301\tabularnewline
$-2LLR (Model \chi^2)$ & 0.208 \tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex12)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{2}{l}@{}}
\hline
&\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 0.033*** \tabularnewline
&(0.001)\tabularnewline
x1 & -0.002* \tabularnewline
&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100} \tabularnewline
RMSE&\tabularnewline
$R^2$&\tabularnewline
Deviance&4.301\tabularnewline
$-2LLR (Model \chi^2)$ & 0.208 \tabularnewline
\hline
\hline
\multicolumn{2}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex13 <- outreg(list("OLS" = m1, "GLM" = gm1), float = TRUE,
+ alpha = c(0.05, 0.01))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245** & 0.033** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex13)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245** & 0.033** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$}\tabularnewline
\end{tabular}
\end{table}
> ##'
> ex14 <- outreg(list(OLS = m1, GLM = gm1), float = TRUE,
+ request = c(fstatistic = "F"), runFuns = c("BIC" = "BIC"))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 0.033*** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{659.82}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> cat(ex14)
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.245*** & 0.033*** \tabularnewline
&(0.618)&(0.001)\tabularnewline
x1 & 1.546* & -0.002* \tabularnewline
&(0.692)&(0.001)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.121 &\tabularnewline
$R^2$&0.048 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.98(1,98)*} &\tabularnewline
Deviance& &4.301\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.208 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{659.82}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
> ex15 <- outreg(list(OLS = m1, GLM = gm1), float = TRUE,
+ request = c(fstatistic = "F"), runFuns = c("BIC" = "BIC"),
+ digits = 5, alpha = c(0.01))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.24550* & 0.03313* \tabularnewline
&(0.61763)&(0.00068)\tabularnewline
x1 & 1.54553 & -0.00173 \tabularnewline
&(0.69242)&(0.00078)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.12090 &\tabularnewline
$R^2$&0.04838 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.9821(1,98)} &\tabularnewline
Deviance& &4.30066\tabularnewline
$-2LLR (Model \chi^2)$ & & 0.20827 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{659.82}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.01$}\tabularnewline
\end{tabular}
\end{table}
>
> ex16 <- outreg(list("OLS 1" = m1, "OLS 2" = m2, GLM = gm1), float = TRUE,
+ request = c(fstatistic = "F"),
+ runFuns = c("BIC" = "BIC", logLik = "ll"),
+ digits = 5, alpha = c(0.05, 0.01, 0.001))
\begin{table}
\caption{A Regression}\label{regrlabl}
\begin{tabular}{@{}l*{4}{l}@{}}
\hline
&\multicolumn{1}{l}{OLS 1 } &\multicolumn{1}{l}{OLS 2 } &\multicolumn{1}{l}{GLM }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 30.24550*** & 29.77420*** & 0.03313*** \tabularnewline
&(0.61763)&(0.52229)&(0.00068)\tabularnewline
x1 & 1.54553* &\multicolumn{1}{l}{\_ }& -0.00173* \tabularnewline
&(0.69242) &&(0.00078)\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.41342*** &\multicolumn{1}{l}{\_ }\tabularnewline
&&(0.51222) &\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE&6.12090 &5.20508 &\tabularnewline
$R^2$&0.04838 &0.31184 &\tabularnewline
adj $R^2$&0.03867 &0.30482 &\tabularnewline
F($df_{num}$,$df_{denom}$)&\multicolumn{1}{c}{4.9821(1,98)*} &\multicolumn{1}{c}{44.409(1,98)***} &\tabularnewline
Deviance& & &4.30066\tabularnewline
$-2LLR (Model \chi^2)$ & & & 0.20827 \tabularnewline
BIC&\multicolumn{1}{c}{657.92} &\multicolumn{1}{c}{625.51} &\multicolumn{1}{c}{659.82}\tabularnewline
ll&\multicolumn{1}{c}{-322.05(3)} &\multicolumn{1}{c}{-305.85(3)} &\multicolumn{1}{c}{-323(3)}\tabularnewline
\hline
\hline
\multicolumn{4}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
\end{table}
>
> ex17 <- outreg(list("Model A" = gm1, "Model B label with Spaces" = m2),
+ request = c(fstatistic = "F"),
+ runFuns = c("BIC" = "Schwarz IC", "AIC" = "Akaike IC",
+ "nobs" = "N Again?"))
\begin{tabular}{@{}l*{3}{l}@{}}
\hline
&\multicolumn{1}{l}{Model A } &\multicolumn{1}{l}{Model B label with Spaces }\tabularnewline
&\multicolumn{1}{l}{Estimate}&\multicolumn{1}{l}{Estimate}\tabularnewline
&\multicolumn{1}{l}{(S.E.)}&\multicolumn{1}{l}{(S.E.)}\tabularnewline
\hline
\hline
(Intercept) & 0.033*** & 29.774*** \tabularnewline
&(0.001)&(0.522)\tabularnewline
x1 & -0.002* &\multicolumn{1}{l}{\_ }\tabularnewline
&(0.001) &\tabularnewline
x2 &\multicolumn{1}{l}{\_ }& 3.413*** \tabularnewline
&&(0.512)\tabularnewline
\hline
N&\multicolumn{1}{l}{100}&\multicolumn{1}{l}{100} \tabularnewline
RMSE& &5.205\tabularnewline
$R^2$& &0.312\tabularnewline
adj $R^2$& &0.305\tabularnewline
F($df_{num}$,$df_{denom}$)& &\multicolumn{1}{c}{44.4(1,98)***}\tabularnewline
Deviance&4.301 &\tabularnewline
$-2LLR (Model \chi^2)$ & 0.208 & \tabularnewline
Schwarz IC&\multicolumn{1}{c}{659.82} &\multicolumn{1}{c}{625.51}\tabularnewline
Akaike IC&\multicolumn{1}{c}{652.00} &\multicolumn{1}{c}{617.69}\tabularnewline
N Again?&\multicolumn{1}{c}{100} &\multicolumn{1}{c}{100}\tabularnewline
\hline
\hline
\multicolumn{3}{l}{ ${* p}\le 0.05$${*\!\!* p}\le 0.01$${*\!\!*\!\!* p}\le 0.001$}\tabularnewline
\end{tabular}
>
> ## Here's a fit example from lme4.
> if (require(lme4) && require(car)){
+ fm1 <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
+ ex18 <- outreg(fm1)
+ cat(ex18)
+ ## Fit same with lm for comparison
+ lm1 <- lm(Reaction ~ Days, sleepstudy)
+ ## Get robust standard errors
+ lm1rse <- sqrt(diag(car::hccm(lm1)))
+
+ if(interactive()){
+ ex19 <- outreg(list("Random Effects" = fm1,
+ "OLS" = lm1, "OLS Robust SE" = lm1),
+ SElist = list("OLS Robust SE" = lm1rse), type = "html")
+ }
+ ## From the glmer examples
+ gm2 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
+ data = cbpp, family = binomial)
+ lm2 <- lm(incidence/size ~ period, data = cbpp)
+ lm2rse <- sqrt(diag(car::hccm(lm2)))
+ ## Lets see what MASS::rlm objects do? Mostly OK
+ rlm2 <- MASS::rlm(incidence/size ~ period, data = cbpp)
+
+ }
Loading required package: lme4
Loading required package: Matrix
Error in get(x, envir = ns, inherits = FALSE) :
object 'formatVC' not found
Calls: outreg ... getVCmat -> lapply -> FUN -> getFromNamespace -> get
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.