R: how can I create a table with mean and sd according to experimental group alongside p-values?

Question

I know how I can do all that for individual variables but I need to report this information for a large number of variables and would like to know if there is an efficient w

Answer 1

In a data object like that offered by Alexander:

 aggregate( . ~ Group, FUN=function(x) c(mn=mean(x), sd=sd(x)), data=Data[-1])
# Output
  Group       V1.mn       V1.sd       V2.mn       V2.sd
1     1  0.05336901  0.85468837  0.06833691  0.94459083
2     2 -0.01658412  0.97583110 -0.02940477  1.11880398
       V3.mn      V3.sd       V4.mn       V4.sd
1 -0.2096497  1.1732246  0.08850199  0.98906102
2  0.0674267  0.8848818 -0.11485148  0.90554914

The data argument omits the ID column because you only want the results on the data columns. The request for a collection of p-values can be accomplished with:

 sapply(names(Data)[-(1:2)], function(x) c( 
                   Mean.Grp1 = mean(Data[Data$Group==1,x]), 
                   Mean.Grp2 = mean(Data[Data$Group==2,x]), 
                   `p-value`= t.test(Data[Data$Group==1, x], 
                                     Data[Data$Group==2,x])$p.value )
          )
#---------------------------
                   V1          V2         V3          V4
Mean.Grp1  0.05336901  0.06833691 -0.2096497  0.08850199
Mean.Grp2 -0.01658412 -0.02940477  0.0674267 -0.11485148
p-value    0.70380932  0.63799544  0.1857743  0.28624585

If you wanted to add the SD's to that output the strategy seems obvious. You should note the back-quoting of the "p-value" name. Minus signs are syntactically "active" and would get interpreted as functions if not enclosed in quotes.