Omit some coefficients from the mtable / outreg-type table

Question

I use a bunch of different regression models and now I would like to get their estimates in the LaTeX table. To compare different specifications, I would like to use the type of table that outreg from the outreg package or mtable from memisc produces, that is, the one in which different models are displayed in columns and parameter estimates from these models are shown in the corresponding rows. This is what I have:

 df <- data.frame(x=rnorm(20), z=rnorm(20), group=gl(5,4,20,labels=paste('group',rep(1:5)))) df$y = 5 + 2*df$x + 5*df$z + rep(c(3.2,5,6.2,8.2,5),each=4) + rnorm(20) model1 <- lm(y ~ x + z + factor(group),data=df) model2 <- lm(y ~ x + factor(group),data=df) model3 <- lm(y ~ x + z,data=df) library(memisc) reg.table <- mtable("Model 1"=model1,"Model 2"=model2,"Model 3"=model3, summary.stats=c("sigma","R-squared","F","p","N")) toLatex(reg.table) 

This works quite well, but I have a factor with about 200 levels and a correspondingly large number of factors. What I would like to do is either omit the coefficients associated with this coefficient from the table, or (for bonus points!), To show that the factor was used in the model with a simple yes or no. So my ideal output would be this:

 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % % Calls: % Model 1: lm(formula = y ~ x + z + factor(group), data = df) % Model 2: lm(formula = y ~ x + factor(group), data = df) % Model 3: lm(formula = y ~ x + z, data = df) % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % \begin{tabular}{lcD{.}{.}{7}cD{.}{.}{7}cD{.}{.}{7}} \toprule &&\multicolumn{1}{c}{Model 1} && \multicolumn{1}{c}{Model 2} && \multicolumn{1}{c}{Model 3}\\ \midrule (Intercept) & & 8.315^{***} && 4.235 && 10.338^{***}\\ & & (0.537) && (3.276) && (0.468) \\ x & & 1.976^{***} && 2.398 && 1.858^{***}\\ & & (0.238) && (1.530) && (0.443) \\ z & & 5.389^{***} && && 5.359^{***}\\ & & (0.226) && && (0.463) \\ group & & yes && yes && no \\ \midrule sigma & & 0.929 && 5.981 && 2.092 \\ R-squared & & 0.984 && 0.265 && 0.891 \\ F & & 129.485 && 1.009 && 69.306 \\ p & & 0.000 && 0.448 && 0.000 \\ N & & 20 && 20 && 20 \\ \bottomrule \end{tabular} 

Is it possible?

Answer 1

A simple definition of the first three coefficients is quite simple:

 reg.table$coefficients <- reg.table$coefficients[,,1:3,,drop=FALSE] toLatex(reg.table) 

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The “bonus” question (i.e. adding the 4th line created manually with the description of the “group”) requires a bit more work:

 ## Select the first three coeffients + one to be modified reg.table$coefficients <- reg.table$coefficients[,,1:4,,drop=FALSE] ## Make a copy of all the coefficients, and in the copy, modify the 4th j <- reg.table$coefficients j[,,4,] <- c("yes", "", "yes", "", "no", "") dimnames(j)[[3]][4] <- "group" ## Put the modified coefficients back into `reg.table` reg.table$coefficients <- j 

et voila

 toLatex(reg.table) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % Calls: % Model 1: lm(formula = y ~ x + z + factor(group), data = df) % Model 2: lm(formula = y ~ x + factor(group), data = df) % Model 3: lm(formula = y ~ x + z, data = df) % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \begin{tabular}{lcD{.}{.}{7}cD{.}{.}{7}cD{.}{.}{7}} \toprule &&\multicolumn{1}{c}{Model 1} && \multicolumn{1}{c}{Model 2} && \multicolumn{1}{c}{Model 3}\\ \midrule (Intercept) & & 8.830^{***} && 9.846^{**} && 10.342^{***} \\ & & (0.626) && (3.272) && (0.442) \\ x & & 2.047^{***} && 1.765 && 1.937^{***} \\ & & (0.244) && (1.276) && (0.319) \\ z & & 5.138^{***} && && 4.847^{***} \\ & & (0.267) && && (0.372) \\ group & & yes && yes && no \\ & & && && \\ \midrule sigma & & 1.204 && 6.310 && 1.812 \\ R-squared & & 0.975 && 0.270 && 0.927 \\ F & & 85.576 && 1.033 && 107.717 \\ p & & 0.000 && 0.436 && 0.000 \\ N & & 20 && 20 && 20 \\ \bottomrule \end{tabular} 

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Edit:

Here I like the version even better. It describes the first OP comment below and uses abind() (e.g. rbind() for arrays) to add group information to an array that I think is cleaner:

 library(abind) j <- reg.table$coefficients groupFac <- array(c("yes", "", "yes", "", "no", ""), dim=c(2,1,3)) nonGroupFacs <- which(!grepl("group", dimnames(j)[[3]])) j <- j[,,nonGroupFacs,,drop=FALSE] j <- abind(j, groupFac, along=3) dimnames(j)[[3]][length(nonGroupFacs)+1] <- "group" reg.table$coefficients <- j toLatex(reg.table)