-1

For example, if I create two tables, both contain multiple kinds of data: numeric (integer), numeric (continuous), and factor (character) like below:

```
a = c('red','yellow','blue','blue','red','blue','yellow','blue','red','red')
b = c(1,2,3,2,3,2,2,2,1,2)
c = c(1023,432.34,775.33,342.78,3241.45,1029,938,837.32, 739.43,649)
d = c(17313,23523.32,89790,98790.45,98792,498792,23984.87,29739,69198,917638.48)
data.t1 = data.frame(a=a, b=b, c=c, response=d)
a = c('blue','blue','yellow','blue','red','red','yellow','red','blue','red')
b = c(2,1,1,3,2,1,3,1,3,2)
c = c(1775.33,8342.78,649,241.45,29,938,1083,4432.34, 3837.32, 2739.43)
d = c(27313,2423.32,8990,18790.45,27792,4982,2384.87,9739,6198,91638.48)
data.t2 = data.frame(a=a,b=b,c=c, response = d)
```

I will have two tables like below:

```
> data.t1
a b c response
1 red 1 1023.00 17313.00
2 yellow 2 432.34 23523.32
3 blue 3 775.33 89790.00
4 blue 2 342.78 98790.45
5 red 3 3241.45 98792.00
6 blue 2 1029.00 498792.00
7 yellow 2 938.00 23984.87
8 blue 2 837.32 29739.00
9 red 1 739.43 69198.00
10 red 2 649.00 917638.48
> data.t2
a b c response
1 blue 2 1775.33 27313.00
2 blue 1 8342.78 2423.32
3 yellow 1 649.00 8990.00
4 blue 3 241.45 18790.45
5 red 2 29.00 27792.00
6 red 1 938.00 4982.00
7 yellow 3 1083.00 2384.87
8 red 1 4432.34 9739.00
9 blue 3 3837.32 6198.00
10 red 2 2739.43 91638.48
```

data.t1 is the data collected at time 1, and data.t2 is data collected at time 2.

so I want to know, which are the key parameter(s) that contributed the most to the change of the "response" var (or vars, if I can scale it that would be nice as well) from data.t1 to data.t2. for example, if the change in variable a & b contributes most to the increasing (or decreasing) trend in the response var from table at t1 to table at t2, i'd like the code to return var a & b.

**note:**
the data i created are completely random, so may not actually display a "trending" but this is more just for my illustration purpose.

**added note:**

The rows correspond to each other here; ie row 6 of data.t1 corresponds to row 6 of data.t2, and I am interested in the change in response in that row "caused by" in some sense the change in the a, b and c variables

Do the rows correspond to each other here? ie row 6 of

`data.t1`

corresponds to row 6 of`data.t2`

, and you are interested in the change in response in that row "caused by" in some sense the change in the`a`

,`b`

and`c`

variables? Could you give a clearer made up example where the "key parameters" are obvious? Otherwise this isn't particularly clear. – Spacedman – 2016-03-30T07:55:37.027yes that is exactly it. i will add that note to my post. thanks for pointing it out @Spacedman – alwaysaskingquestions – 2016-03-30T16:29:53.300