Linear regression on subsets of data corresponding to two factor combination
1
0
Entering edit mode
5.1 years ago
botinky • 0

In R I am trying to execute linear regressions of Predator.mass/Prey.mass within the subsets of Lifestage and Feeding Interaction. The data I have currently look like this:

|      | Predator.lifestage | Type.of.feeding.interaction | Predator.mass | Prey.mass |
|------|--------------------|-----------------------------|---------------|-----------|
| 1    | adult              | predacious/piscivorous      | 1540          | 14.3      |
| 2    | adult              | predacious/piscivorous      | 1600          | 6.02      |
| 3    | adult              | predacious/piscivorous      | 1840          | 11.9      |
| 4    | adult              | predacious/piscivorous      | 87.6          | 8.12      |
| 5    | adult              | predacious/piscivorous      | 63.9          | 6.56      |
| 6    | adult              | predacious/piscivorous      | 79.2          | 5.41      |
| 7    | adult              | predacious/piscivorous      | 71.2          | 4.45      |
| 8    | adult              | predacious/piscivorous      | 92.1          | 5.98      |

The list of lifestages goes down to include a total of six factors (adult, juvenline etc.) and feeding interactions go down to include a total of five factors (predacious/piscivorous, insectivorous etc.).

So what I want to achieve is a linear regression of Predator.mass/Prey.mass for each combination of subsets (adult, predacious/piscivorous; juvenile, predacious/piscivorous; lavar, predacious/piscivorous... and so on through the lifestages and feeding interactions).

What I'm trying to do is use a for loop and this is what I've got so far...

for (Type.of.feeding.interaction in My_Data) {
                for (Predator.lifestage in My_Data) {
                LinMod <- lm(Predator.mass ~ Prey.mass)
        }
      }

When I run this says object 'Predator.mass' not found. I've only been using coding a couple of weeks so I'm still fumbling around in the dark a bit. I'd really appreciate any help with this! Thank you :)

R linear-regression for-loops subset • 1.1k views
ADD COMMENT
0
Entering edit mode

try :

with (My_Data, for (Type.of.feeding.interaction in My_Data) {
                for (Predator.lifestage in My_Data) {
                LinMod <- lm(Predator.mass ~ Prey.mass)
        }
      }
)

is this what you are looking for:

> df
  Predator.lifestage Type.of.feeding.interaction Predator.mass Prey.mass
1              adult      predacious/piscivorous        1540.0     14.30
2              adult      predacious/piscivorous        1600.0      6.02
3              adult      predacious/piscivorous        1840.0     11.90
4              adult      predacious/piscivorous          87.6      8.12
5              adult      predacious/piscivorous          63.9      6.56
6              adult      predacious/piscivorous          79.2      5.41
7              adult      predacious/piscivorous          71.2      4.45
8              adult      predacious/piscivorous          92.1      5.98

> library(dplyr)
> library(broom)
> df %>%
       group_by(Type.of.feeding.interaction, Predator.lifestage) %>%
       group_map(~ tidy(lm(Predator.mass ~ Prey.mass, .)))
# A tibble: 2 x 7
# Groups:   Type.of.feeding.interaction, Predator.lifestage [1]
  Type.of.feeding.interaction Predator.lifestage term        estimate std.error statistic p.value
  <chr>                       <chr>              <chr>          <dbl>     <dbl>     <dbl>   <dbl>
1 predacious/piscivorous      adult              (Intercept)    -618.     593.      -1.04  0.338 
2 predacious/piscivorous      adult              Prey.mass       164.      69.9      2.35  0.0568
ADD REPLY
0
Entering edit mode

Hi there, cheers for your reply! I've applied it to my data set and it works, just as you said. Thanks again and have a great day :)

ADD REPLY
1
Entering edit mode
5.1 years ago
Sam ★ 4.8k

Assuming your file is called data.txt

library(data.table)
dat <- fread("data.txt")
results <- dat[,.(Pvalue=summary(lm(Predator.mass~Prey.mass))$coefficient[2,4], 
          beta=summary(lm(Predator.mass~Prey.mass))$coefficient[2,3], 
          r2=summary(lm(Predator.mass~Prey.mass))$r.squared),
          by=c("Predator.lifestage","Type.of.feeding.interaction")]

Should give you the expected results.

ADD COMMENT
0
Entering edit mode

Hi Sam, thank you so much for taking the time to respond to my question! I'm affraid when I tried to run the code I got this error message: Error in summary(lm(Predator.mass ~ Prey.mass))$coefficient[2, 4] : subscript out of bounds

ADD REPLY

Login before adding your answer.

Traffic: 1801 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6