Dear All

Sorry for this simple question, I could not solve it by spending days.

My data looks like this:

# data
set.seed(1234)
clvar <- c( rep(1, 10), rep(2, 10), rep(3, 10), rep(4, 10)) # I have 100
level for this factor var;
yvar <-  rnorm(40, 10,6);
var1 <- rnorm(40, 10,4); var2 <- rnorm(40, 10,4); var3 <- rnorm(40, 5, 2);
var4 <- rnorm(40, 10, 3); var5 <- rnorm(40, 15, 8) # just example
df <- data.frame(clvar, yvar, var1, var2, var3, var4, var5)

# manual splitting
df1 <- subset(df, clvar == 1)
df2 <- subset(df, clvar == 2)
df3<- subset(df, clvar == 3)
df4<- subset(df, clvar == 4)
df5<- subset(df, clvar == 5)

# i tried to mechanize it
*

for(i in 1:5) {

          df[i] <- subset(df, clvar == i)

}

I know it should not work as df[i] is single variable, do it did. But I
could not find away to output multiple dataframes from this loop. My limited
R knowledge, did not help at all !

*

# working on each of variable, just trying simple function
 a <- 3:8
out1 <- lapply(1:5, function(ind){
                   lm(df1$yvar ~ df1[, a[ind]])
 })
p1 <- lapply(out1, function(m)summary(m)$coefficients[,4][2])
p1 <- do.call(rbind, p1)


My ultimate objective is to apply this function to all the dataframes
created (i.e. df1, df2, df3, df4, df5) and create five corresponding p-value
vectors (p1, p2, p3, p4, p5). Then output would be a matrix of clvar and
correponding p values
clvar       var1   var2  var3  var4   var5
1
2
3
4

Please help me !

Thanks

NIL

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