Hi everyone,

 

I'm helping some colleagues with analyzing behavioral data. The
experiment was to repeatedly remove seeds that animals have cached and
see what they do after a number of trials (control + 9).

 

Here's some of the code for the repeated measures:

 

squirrel <- read.csv("h:/temp/squirrel.csv", header=T)

sex <- factor(squirrel$sex)

library(nlme)

squirrel.ar1 <- gls(removed ~ trial + sex + trial*sex, data = squirrel,

  corr = corAR1(, form= ~ 1 | id))

summary(squirrel.ar1)

 

They asked me to compare each trial (2 - 9) to the first trial.  I
simply did a paired t-test but I wasn't sure where to go from there.
Should I simply do a Bonferroni correction or is there a better
approach?

 

Below are some sample data.

 

Thanks a bunch!

 

Jeff

 

 

 

id

trial

sex

removed

eaten

scatter

1

1

2

3.32

2

2.65

2

1

2

4

0

4

3

1

2

1.41

0

1.41

4

1

2

3

2.65

1.41

5

1

1

2

0

1.73

6

1

1

5.48

0

5.48

7

1

1

3.32

1

3

8

1

1

3.61

0

3.46

1

2

2

3.61

2.83

2.24

2

2

2

4

0

4

3

2

2

1

0

1

4

2

2

4.24

3.74

2

5

2

1

1.41

0

1.41

6

2

1

5.48

2.45

4.9

7

2

1

3.74

2.24

3

8

2

1

3.61

2

3

1

3

2

4.24

4

1.41

2

3

2

4.12

0

4.12

3

3

2

2.24

1.73

1.41

4

3

2

4.12

4

1

5

3

1

1.41

1

1

6

3

1

5.48

4

3.74

7

3

1

4

3

2.65

8

3

1

3.74

2.83

2.45

 

 

*****************************************

Jeffrey A. Stratford, Ph.D.

Department of Health and Biological Sciences

84 W. South St.

Wilkes University, PA 18766

570-332-2942

http://web.wilkes.edu/jeffrey.stratford/

*****************************************




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