cbpp2
(Package: glmm) :
Contagious bovine pleuropneumonia
This data set is a reformatted version of cbpp from the lme4 package. 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).
● Data Source:
CranContrib
● Keywords: generalized linear mixed models
● Alias: cbpp2
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murder
(Package: glmm) :
Number of Homicide Victims Known
Subjects responded to the question 'Within the past 12 months, how many people have you known personally that were victims of homicide?'
● Data Source:
CranContrib
● Keywords: generalized linear mixed models
● Alias: murder
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bernoulli.glmm
(Package: glmm) :
Functions for the Bernoulli family.
Given a scalar eta, this calculates the cumulant and two derivatives for the Bernoulli family. Also checks that the data are entered correctly.
● Data Source:
CranContrib
● Keywords: Monte Carlo likelihood approximation, generalized linear mixed model
● Alias: bernoulli.glmm
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bacteria
(Package: glmm) :
Presence of Bacteria after Drug Treatments
Tests of the presence of the bacteria H. influenzae in children with otitis media in the Northern Territory of Australia.
● Data Source:
CranContrib
● Keywords: generalized linear mixed models
● Alias: bacteria
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BoothHobert
(Package: glmm) :
A Logit-Normal GLMM Dataset from Booth and Hobert
This data set contains simulated data from the paper of Booth and Hobert referenced below.
● Data Source:
CranContrib
● Keywords: generalized linear mixed models
● Alias: BoothHobert
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glmm
(Package: glmm) :
Fitting Generalized Linear Mixed Models using MCML
This function fits generalized linear mixed models (GLMMs) by approximating the likelihood with ordinary Monte Carlo, then maximizing the approximated likelihood.
● Data Source:
CranContrib
● Keywords: Monte Carlo, generalized linear mixed model, likelihood approximation, maximum likelihood
● Alias: glmm
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summary.glmm
(Package: glmm) :
Summarizing GLMM Fits
"summary" method for class glmm objects.
● Data Source:
CranContrib
● Keywords: Monte Carlo, generalized linear mixed models, maximum likelihood, models
● Alias: print.summary.glmm, summary.glmm
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poisson.glmm
(Package: glmm) :
Functions for the Poisson family.
Given a scalar eta, this calculates the cumulant and two derivatives for the Poisson family. Also checks that the data are entered correctly.
● Data Source:
CranContrib
● Keywords: Monte Carlo likelihood approximation, generalized linear mixed model
● Alias: poisson.glmm
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Booth2
(Package: glmm) :
A Logit-Normal GLMM Dataset
This data set contains simulated data from the paper of Booth and Hobert (referenced below) as well as another vector.
● Data Source:
CranContrib
● Keywords: generalized linear mixed models
● Alias: Booth2
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varcomps
(Package: glmm) :
Extract Model Variance Components
A function that extracts the variance components returned from glmm.
● Data Source:
CranContrib
● Keywords: generalized linear mixed model
● Alias: varcomps
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