Re: [R] how to assing unique ID in a table and do regression

[Rui Barradas]

Sorry, forgot to Cc the list.

Em 06-08-2012 17:29, Rui Barradas escreveu:

Hello,

I'm glad it helped.

The result of function cut() is a factor variable so you can coerce it to integer, giving more "normal" names, or, if you want to keep track of the intervals the adjusted r2 belong to, got straight to the last two lines in the following code.

#dat1$groups <- as.integer( cut( ...etc... ) )

[...rest of your code... ]

adj <- summary(lin.temp1)$adj.r.squared
class(adj) <- "list"

That's it. It has as names the intervals produced by cut that appear in the output you've posted.

Rui Barradas

Em 06-08-2012 17:07, Kristi Glover escreveu:

Dear Rui,
Thanks for the help. I really appricated . It helped me out.

I modified some of the script you gave me becasue I found the package 'nlme' can also do it. But I do use the script you gave me to split the data

  dat1$groups<-cut(dat1$LATITUDE, seq(-56,79, by=2.5))
lin.temp1<-lmList(S~mean_temp|groups,data=dat1)

could you please give me an idea how I can extract r adjusted and put them in a table? I called summary but it gave me the value of r2 adjusted for each group but I don't know how I can put teh r2 adjusted in table (like: group , r2 sqaure, r2 adjusted)

summary(lin.temp1)$adj.r.squared

(-56,-53.5] :
[1] 0.2565786
(-53.5,-51] :
[1] 0.0715485
(-51,-48.5] :
[1] 0.2265334

Thanks
Kristi

Date: Sat, 4 Aug 2012 16:15:57 +0100
From: ruipbarra...@sapo.pt
To: kristi.glo...@hotmail.com
CC: r-help@r-project.org
Subject: Re: [R] how to assing unique ID in a table and do regression

Hello,

Try the following.


id.groups <- with(dat, cut(ID, breaks=0:ceiling(max(ID))))
sp <- split(dat, id.groups)
regressors <- grep("en", names(dat))
models <- lapply(sp, function(.df)
      lapply(regressors, function(x) lm(.df[["S"]] ~ .df[[x]])))

mod.summ <- lapply(models, function(x) lapply(x, summary))
# First R2
mod.r2 <- lapply(mod.summ, function(x) lapply(x, `[[`, "r.squared"))
mod.r2

# Now p-values
mod.coef <- lapply(mod.summ, function(x) lapply(x, coef))
mod.pvalue <- lapply(mod.coef,  function(x) lapply(x, `[`, , 4))
# p-values in matrix form, columns are 'en2', en3', etc
#lapply(mod.pvalue, function(x) do.call(cbind, x))

Hope this helps,

Rui Barradas

Em 04-08-2012 15:22, Kristi Glover escreveu:

Hi R- User

I have very big data set (5000 rows). I wanted to make classes based on a column of that table (that column has the data which is continuous .) After converting into different class, this class would be Unique ID. I want to run regression for each ID.

For example I have a data set

dput(dat)

structure(list(ID = c(0.1, 0.8, 0.1, 1.5, 1.1, 0.9, 1.8, 2.5,
2, 2.5, 2.8, 3, 3.1, 3.2, 3.9, 1, 4, 4.7, 4.3, 4.9, 2.1, 2.4),
      S = c(4L, 7L, 9L, 10L, 10L, 8L, 8L, 8L, 17L, 18L, 13L, 13L,

11L, 1L, 10L, 20L, 22L, 20L, 18L, 16L, 7L, 20L), en2 = c(-2.5767,

      -2.5767, -2.5767, -2.5767, -2.5767, -2.5767, -2.5767, -2.5347,
      -2.5347, -2.5347, -2.5347, -2.5347, -2.5347, -2.4939, -2.4939,
      -2.4939, -2.4939, -2.4939, -2.4939, -2.4939, -2.4543, -2.4543
      ), en3 = c(-1.1785, -0.6596, -0.6145, -0.6437, -0.6593, -0.7811,
      -1.1785, -1.1785, -1.1785, -0.6596, -0.6145, -0.6437, -0.6593,
      -1.1785, -0.1342, -0.2085, -0.4428, -0.5125, -0.8075, -1.1785,
      -1.1785, -0.1342), en4 = c(-1.4445, -1.3645, -1.1634, -0.7735,
      -0.6931, -1.1105, -1.4127, -1.5278, -1.4445, -1.3645, -1.1634,
      -0.7735, -0.6931, -1.0477, -0.8655, -0.1759, 0.1203, -0.2962,
      -0.4473, -1.0436, -0.9705, -0.8953), en5 = c(-0.4783, -0.3296,
      -0.2026, -0.3579, -0.5154, -0.5726, -0.6415, -0.3996, -0.4529,
      -0.5762, -0.561, -0.6891, -0.7408, -0.6287, -0.4337, -0.4586,

-0.5249, -0.6086, -0.7076, -0.7114, -0.4952, 0.1091)), .Names = c("ID", "S", "en2", "en3", "en4", "en5"), class = "data.frame", row.names = c(NA,

-22L))

Here ID has continuous value, I want to make groups with value 0-1, 1-2, 2-3, 3-4 from the column ID. and then. I wanted to run regression with S (dependent variable) and en2 (independent variable); again regression of S and en3 , and so on.

After that, I wanted to have a table with r2 and p value.

would you help me how I can do it? I was trying it manually - but it took so much time. therefore I thought to write you for your help.

Thanks for your help.
Kristi




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