- using R version 4.6.0 alpha (2026-03-26 r89725)
- using platform: aarch64-apple-darwin23
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Apple clang version 17.0.0 (clang-1700.3.19.1)
GNU Fortran (GCC) 14.2.0
- running under: macOS Sequoia 15.7.1
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* current time: 2026-03-27 16:26:23 UTC
- checking for file ‘rockchalk/DESCRIPTION’ ... OK
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- this is package ‘rockchalk’ version ‘1.8.157’
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See the install log for details.
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- checking dependencies in R code ... OK
- checking S3 generic/method consistency ... OK
- checking replacement functions ... OK
- checking foreign function calls ... OK
- checking R code for possible problems ... [4s/4s] OK
- checking Rd files ... [0s/0s] NOTE
checkRd: (-1) descriptiveTable.Rd:18: Lost braces
18 | other object type that does not fail in code{model.frame(object)}.}
| ^
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- checking examples ... [2s/2s] 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
- checking for unstated dependencies in vignettes ... OK
- checking package vignettes ... OK
- checking re-building of vignette outputs ... [26s/26s] OK
- checking PDF version of manual ... [3s/3s] OK
- DONE
Status: 1 ERROR, 1 NOTE
- using check arguments '--no-clean-on-error '