# [R] RES: Linear regression - several response variables vs few indvariables

From: Filipe Leme Botelho <filipe.botelho_at_vpar.com.br>
Date: Tue, 31 May 2011 13:03:06 -0300

attached mail follows:

Hi Raphael, using your data as is, and if I understood what you need

> birds

```     Square Sp1 Sp2 Sp3 Sp4 Spn Natprop Effort

[1,]      1   1   0   1   1   0     0.5     10
[2,]      2   1   0   1   1   0     0.6     20
[3,]      3   1   1   0   1   0     0.8     23
[4,]      4   1   0   1   0   0     0.8     50

[5,]      5   0   1   0   1   1     0.9     30

I store all results from regressions in a list to then extract
```
what I want

bird_regressions <- lapply(1:5, function(i) lm(birds[,i+1] ~ birds[, "Natprop"] + birds[, "Effort"]))
# Will just loop through Sp1, Sp2... Spn keeping "Natprop" and "Effort" fixed

Now retrieving some important stats

r_sq <- sapply(1:length(bird_regressions),function(i) summary(bird_regressions[[i]])\$r.squared) betas <- sapply(1:length(bird_regressions),function(i) summary(bird_regressions[[i]])\$coefficients[2,1]) tstat <- sapply(1:length(bird_regressions),function(i) summary(bird_regressions[[i]])\$coefficients[2,3])

Now with

cbind(r_sq, betas, tstat)

You will have a matrix summarizing what I believe you need from Sp1, Sp2... Spn. Hope this was helpful.

-----Mensagem original-----
De: r-help-bounces_at_r-project.org [mailto:r-help-bounces_at_r-project.org] Em nome de Rafael Xavier de Camargo
Enviada em: segunda-feira, 23 de maio de 2011 13:05 Para: r-help_at_r-project.org
Assunto: [R] Linear regression - several response variables vs few indvariables

Hi all,

I need to run several simple linear regressions at once, using the following data. Response variables: Bird species (sp 1, sp2, sp3...spn). Independent variable: Natprop - proportion of natural area. covarate: Effort = hours). One single linear regression would be: lmSp1 <- lm(sp1~ natprop + effort). However, I need to run this linear regression for all bird species that I have individually (n = 163). I would like to do it at
once and store the coefficients in a single data frame. Is that possible?

Table that I have:
Square Sp1 Sp2 Sp3 Sp4 Spn Natprop Effort

```1        1    0    1   1    0     0.5     10
2        1    0    1   1    0     0.6     20
3        1    1    0   1    0     0.8     23
4        1    0    1   0    0     0.8     50
n        0    1    0   1    1     0.9     30

```

Rafael.

RAFAEL CAMARGO
Biology Department of University of Ottawa 30 Marie Curie, room # 351
Tel: +1 (613) 562-5800 ext. 6366
Cel: +1 (613) 869-3772
e-mail: rcama081_at_uottawa.ca

rafael.x.camargo_at_gmail.com

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