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> ### 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