The effect of a GnRH vaccine, GonaConTM
on the growth of juvenile tammar wallabies
1Bob
Forrester, 2 Melissa Snape and 2Lyn A. Hinds
1Statistical
Consulting Unit, ANU, Canberra, ACT
2 Invasive Animals CRC, Canberra, ACT
Outline of talk
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Introduction
Data
Questions of interest
Modelling growth responses
Concluding remarks
Introduction
Vaccination against gonadotrophin releasing hormone
disrupts hormonal regulation of reproduction
GonaConTM is effective in eutherian mammals (eg deer,
horses, bison)
Tested here on marsupials (Tammar wallabies – relatively
small and easy to handle)
Introduction – why vaccinate animals?
Control of overabundant populations
eg Possums in New Zealand, kangaroos in Australia
More humane than poison baits
Avoids emotional responses
More politically acceptable
Data
35 juvenile male Tammar wallabies
3 treatments – sham control, Vac1 (week 0), Vac2 (week 0
and week4)
12 variables measured
Key variables associated with testes size
20 measurement times, up to 131 weeks after treatment
Data
Repeated measurements
Unequally spaced intervals
All animals measured at the same time
Two animals have incomplete records (both animals died)
All analyses carried out using GenStat
Tammar wallabies
120
110
100
90
80
0
20
40
60
Week
80
100
120
Testes volume
Tammar wallabies
25
20
15
10
5
0
0
20
40
60
Week
80
100
120
Tammar wallabies
3
2
1
0
-1
0
20
40
60
Week
80
100
120
Data
Week
Interval
0
Week
Interval
Week
Interval
79
8
7
7
11
4
15
4
19
4
24
5
28
4
34
6
40
6
48
8
54
6
62
8
71
9
91
12
101
10
108
7
115
7
123
6
131
8
Questions of interest
Is the vaccine effective?
Is Vac2 more effective than Vac1?
Does the effectiveness wear off over time?
Are body measurements other than testes affected?
Summary statistics approach
Method effective for measurements such as arm length
Answers overall question of treatment effect
Does not explore treatment interaction with time
Cannot handle the complex responses observed in testes
measurements
Fitting problems with short response runs
Arm length – exponential model
Arm length = A + B*R**Weeks , R = exp(-K)
Means
Parameter Control
Vac1
Vac2
SED
A
130.4
110.2
105.5
3.13
B
-48.7
-27.6
-23.2
2.91
R
0.98891
0.986 0.98538 0.001315
Model variance structure
Measurements unequally spaced, but all animals measured
at the same time
Antedependence or power models
Fixed effects of Treatment, Week, Treatment.Week
Suitable for arm length and also testes measurements
Arm length
Antedependence model order 1 (change of deviance)
Additional animal variance component (9.219, SE=2.331)
Fixed term
week
treatment
week.treatment
Wald statistic
d.f.
Wald/d.f.
3389.51
19
178.4
174.73
2
87.37
359.66
38
9.46
chi pr
<0.001
<0.001
<0.001
Arm length
week
Control
Vac1
Vac2
0
85.67
84.4
83.92
7
85.02
85.67
83.59
101
108
115
123
131
114.78
115.43
116.01
116.42
117.28
102.42
102.33
103
103.55
104.17
100.22
99.68
100.58
100.83
101.41
Greater insight into treatment effects over time
Av. SED
1.204
ln(Testes volume)
Log transform needed to stabilize the variance
Antedependence order 1 model
When variance component included for animal, estimation
problems with week 115
Antedependence order 2 model better, but effect on the
predicted means is slight (smaller SED)
ln(Testes volume)
week
0
7
11
15
19
24
115
123
131
Control
Vac1
Vac2
Av. SED
0.258
0.791
0.566
0.2245
0.957
0.536
0.197
1.366
0.314
0.084
1.485
-0.038
-0.298
1.907
0.032
-0.192
2.096
0.013
-0.265
2.953
3.025
3.078
0.789
0.995
1.015
0.503
0.684
0.777
ln(Testes volume)
Significant interaction due to lack of differences until week 11
Large differences between treated and untreated animals
thereafter
No significant differences between Vac 1 and Vac 2 at any
stage
One Vac 1 animal effect perhaps wearing off
Tammar wallabies
3
2
1
0
-1
0
20
40
60
Week
80
100
120
Concluding remarks
Two methods for analysing repeated measures data used on
Tammar wallaby data
Summary statistics work well with smooth data
More complex method required to explore interactions over
time and with data that is not smooth