This may not be exactly what you hoped for, but you can transform the coefficients, and give stargazer a custom list of coefficients. For example, if you would like to report the coefficient times the standard deviation of each variable, the following extension of your example could work: library(foreign) library(stargazer)...

# Rename intercept names(lm_model$coefficients)[1] # Change value of intercept to control_mean lm_model$coefficients[1] = control_mean This isn't really a stargazer question, but is just a matter of how to modify a model object....

You could extract the coefficients and their standard errors and then feed that to stargazer: model.summary = coef(summary(model))[, 1:2] stargazer(model.summary, flip=TRUE) Here's what the PDF output looks like: ...

r,table,scientific-notation,stargazer,coefficients

Here's a reproducible example: m1 <- lm(Sepal.Length ~ Petal.Length*Sepal.Width, transform(iris, Sepal.Length = Sepal.Length+1e6, Petal.Length=Petal.Length*10, Sepal.Width=Sepal.Width*100)) # Coefficients: # (Intercept) Petal.Length Sepal.Width Petal.Length:Sepal.Width # 1.000e+06 7.185e-02 8.500e-03 -7.701e-05 I don't believe stargazer has easy support for this. You could try other alternatives like xtable or any of the many options here...

Maybe you can do some adaptation of this: ifelse(x < 100, sprintf("%0.2f", x), sprintf("%0.5e", x)) # [,1] [,2] [,3] [,4] [,5] #[1,] "9.99999e+06" "-0.79" "-0.56" "0.91" "-2.57" #[2,] "-0.13" "9.99999e+06" "-1.83" "-0.34" "1.73" #[3,] "-0.48" "0.38" "1.00000e+07" "1.40" "-0.32" #[4,] "-0.05" "-0.62" "0.91" "1.00000e+07" "1.15" #[5,] "-0.09" "-0.33" "-0.16" "0.35"...

At the moment you could get your desires under the condition that those were the names of the model-objects, but not if they had other names, by doing this: stargazer( hhc,dca,bpc, object.names=TRUE, model.numbers=FALSE) This was tested with the first example in the help page: stargazer(linear.1, linear.2, probit.model, title="Regression Results", type="text",...

The latest version 1.34.3 of the texreg package supports both model.selection and averaging objects. Your code example: library("texreg") library("MuMIn") data(cement) fm1 <- lm(y ~ ., data = Cement, na.action = na.fail) ms1 <- dredge(fm1) screenreg(ms1) yields: ========================================================================================================================================================================================================== Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model...

You need to provide the p values associated with your coeftest. From the man page. p a list of numeric vectors that will replace the default p-values for each model. Matched by element names. These will form the basis of decisions about significance stars The following should work. test <-...

Try: x <- sub("\\caption{The main caption of the table.}", "\\caption[short caption]{The main caption of the table.}", fixed = TRUE, x) ...