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  • checking examples ... [13s] 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 ... [142s] OK
  • checking PDF version of manual ... [22s] OK
  • checking HTML version of manual ... [14s] OK
  • DONE Status: 1 ERROR, 1 NOTE Check process probably crashed or hung up for 20 minutes ... killed Most likely this happened in the example checks (?), if not, ignore the following last lines of example output: > ## 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 ======== End of example output (where/before crash/hang up occured ?) ========