Rafael Xavier de Camargo
2011-May-23 16:04 UTC
[R] Linear regression - several response variables vs few ind variables
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
Thanks in advance.
Rafael.
**********************************************
RAFAEL CAMARGO
Postgraduate Student
Biology Department of University of Ottawa
30 Marie Curie, room # 351
Ottawa, ON, CANADA
Tel: +1 (613) 562-5800 ext. 6366
Cel: +1 (613) 869-3772
e-mail: rcama081 at uottawa.ca
rafael.x.camargo at gmail.com
RAFAEL CAMARGO
2011-May-23 16:20 UTC
[R] Linear regression - several response variables vs few ind variables
Hi Everyone,
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
Thanks in advance.
Rafael.
**********************************************
RAFAEL CAMARGO
Postgraduate Student
Biology Department of University of Ottawa
30 Marie Curie, room # 351
Ottawa, ON, CANADA
Tel: +1 (613) 562-5800 ext. 6366
Cel: +1 (613) 869-3772
e-mail: rcama081@uottawa.ca
rafael.x.camargo@gmail.com
[[alternative HTML version deleted]]
Filipe Leme Botelho
2011-May-31 16:03 UTC
[R] RES: Linear regression - several response variables vs few indvariables
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