\begin{Schunk}
\begin{Sinput}
 ## Since 15 years ago, R's default t-test uses Welch's
 ## correction for difference in variance.
 
 ## A replacement for the t-test function
 conductTtest <- function (dframe, y = "IQ", x = "first"){
   	t.test(formula(paste(y, "~", x)), data = dframe)$p.value
  }
 set.seed(123)
 bigResults <- lapply(1:NROW(conds), runOneCondition, conds)
 stackedResults <- do.call(rbind, bigResults)
 ## Now summarize the rejection rate for each condition
 output <- aggregate(reject ~ N + SD, data = stackedResults, FUN = mean)
 names(output) <- c("N", "SD", "Type.I.Rate")
 output
\end{Sinput}
\begin{Soutput}
      N    SD Type.I.Rate
1 30:30 10:20       0.040
2 40:20 10:20       0.047
3 30:30 15:15       0.053
4 40:20 15:15       0.048
5 30:30 20:10       0.041
6 40:20 20:10       0.047
\end{Soutput}
\end{Schunk}
