Use all variables in a model with {plm} in R

Question

Using different sources, I wrote a little function that creates a table with standard errors, t statistics and standard errors that are clustered according to a group variable "cluster" after a linear regression model. The code is as follows

cl1 <- function(modl,clust) {
 # model is the regression model
 # clust is the clustervariable
 # id is a unique identifier in ids
    library(plm)
    library(lmtest)
        #  Get Formula
    form <- formula(modl$call)
        # Get Data frame
    dat <- eval(modl$call$data)
    dat$row <- rownames(dat)
    dat$id <- ave(dat$row, dat[[deparse(substitute(clust))]], FUN =seq_along)       
    pdat <- pdata.frame(dat, 
         index=c("id", deparse(substitute(clust)))
         , drop.index= F, row.names= T)
    # # Regression
      reg <- plm(form, data=pdat, model="pooling")  
    # # Adjustments
     G <- length(unique(dat[, deparse(substitute(clust))]))
     N <- length(dat[,deparse(substitute(clust))])
    # # Resid degrees of freedom, adjusted
     dfa <- (G/(G-1))*(N-1)/reg$df.residual
     d.vcov <- dfa* vcovHC(reg, type="HC0", cluster="group", adjust=T)
    table <- coeftest(reg, vcov=d.vcov)
    # #  Output: se, t-stat and p-val
     cl1out <- data.frame(table[, 2:4])
     names(cl1out) <- c("se", "tstat", "pval")
    # # Cluster VCE
     return(cl1out)

}

For a regression like reg1 <- lm (y ~ x1 + x2 , data= df), calling the function cl1(reg1, cluster) will work just fine.

However, if I use a model like reg2 <- lm(y ~ . , data=df), I will get the error message:

Error in terms.formula(object) : '.' in formula and no 'data' argument

After some tests, I am guessing that I can't use "." to signal "use all variables in the data frame" for {plm}. Is there a way I can do this with {plm}? Otherwise, any ideas on how I could improve my function in a way that does not use {plm} and that accepts all possible specifications of a linear model?

The way you have this set up, y~. will (try to...) include all the columns of pdat except y, but including row, id and clust. Are you sure this is what you want to do? — jlhoward
Oh, thanks! Trying to solve my "." bug I had not seen this one! — Doon_Bogan

agstudy agstudy · Accepted Answer · 2014-10-03T17:27:54

Indeed you can't use . notation for formula within plm pacakge.

data("Produc", package = "plm")
plm(gsp ~ .,data=Produc)
Error in terms.formula(object) : '.' in formula and no 'data' argument

One idea is to expand the formula when you have a .. Here is a custom function that does the job (surely is done within other packages):

expand_formula <- 
  function(form="A ~.",varNames=c("A","B","C")){
  has_dot <- any(grepl('.',form,fixed=TRUE))
  if(has_dot){
    ii <- intersect(as.character(as.formula(form)),
          varNames)
    varNames <- varNames[!grepl(paste0(ii,collapse='|'),varNames)]

   exp <- paste0(varNames,collapse='+')
   as.formula(gsub('.',exp,form,fixed=TRUE))

  }
  else as.formula(form)
}

Now test it :

(eform = expand_formula("gsp ~ .",names(Produc)))
#    gsp ~ state + year + pcap + hwy + water + util + pc + emp + unemp

plm(eform,data=Produc)

# Model Formula: gsp ~ state + year + pcap + hwy + water + util + pc + emp + unemp
# <environment: 0x0000000014c3f3c0>

Use all variables in a model with {plm} in R

1 Answers