Description Format Details Source Examples

Contagious bovine pleuropneumonia (CBPP) is a major disease of cattle in Africa, caused by a mycoplasma. This dataset describes the serological incidence of CBPP in zebu cattle during a follow-up survey implemented in 15 commercial herds located in the Boji district of Ethiopia. The goal of the survey was to study the within-herd spread of CBPP in newly infected herds. Blood samples were quarterly collected from all animals of these herds to determine their CBPP status. These data were used to compute the serological incidence of CBPP (new cases occurring during a given time period). Some data are missing (lost to follow-up).

A data frame with 56 observations on the following 4 variables.

`herd`

A factor identifying the herd (1 to 15).

`incidence`

The number of new serological cases for a given herd and time period.

`size`

A numeric vector describing herd size at the beginning of a given time period.

`period`

A factor with levels

`1`

to`4`

.

Serological status was determined using a competitive enzyme-linked immuno-sorbent assay (cELISA).

Lesnoff, M., Laval, G., Bonnet, P., Abdicho, S.,
Workalemahu, A., Kifle, D., Peyraud, A., Lancelot, R.,
Thiaucourt, F. (2004) Within-herd spread of contagious
bovine pleuropneumonia in Ethiopian highlands.
*Preventive Veterinary Medicine* **64**, 27–40.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
## response as a matrix
(m1 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
family = binomial, data = cbpp))
## response as a vector of probabilities and usage of argument "weights"
m1p <- glmer(incidence / size ~ period + (1 | herd), weights = size,
family = binomial, data = cbpp)
## Confirm that these are equivalent:
stopifnot(all.equal(fixef(m1), fixef(m1p), tolerance = 1e-5),
all.equal(ranef(m1), ranef(m1p), tolerance = 1e-5))
## GLMM with individual-level variability (accounting for overdispersion)
cbpp$obs <- 1:nrow(cbpp)
(m2 <- glmer(cbind(incidence, size - incidence) ~ period + (1 | herd) + (1|obs),
family = binomial, data = cbpp))
``` |

```
Loading required package: Matrix
Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula: cbind(incidence, size - incidence) ~ period + (1 | herd)
Data: cbpp
AIC BIC logLik deviance df.resid
194.0531 204.1799 -92.0266 184.0531 51
Random effects:
Groups Name Std.Dev.
herd (Intercept) 0.6421
Number of obs: 56, groups: herd, 15
Fixed Effects:
(Intercept) period2 period3 period4
-1.3983 -0.9919 -1.1282 -1.5797
Generalized linear mixed model fit by maximum likelihood (Laplace
Approximation) [glmerMod]
Family: binomial ( logit )
Formula: cbind(incidence, size - incidence) ~ period + (1 | herd) + (1 |
obs)
Data: cbpp
AIC BIC logLik deviance df.resid
186.6383 198.7904 -87.3192 174.6383 50
Random effects:
Groups Name Std.Dev.
obs (Intercept) 0.8911
herd (Intercept) 0.1840
Number of obs: 56, groups: obs, 56; herd, 15
Fixed Effects:
(Intercept) period2 period3 period4
-1.500 -1.226 -1.329 -1.866
```

lme4 documentation built on April 4, 2018, 1:04 a.m.

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