clusbootglm {ClusterBootstrap} | R Documentation |
Fit a generalized linear model with the cluster bootstrap for analysis of clustered data.
clusbootglm( model, data, clusterid, family = gaussian, B = 5000, confint.level = 0.95, n.cores = 1 )
model |
generalized linear model to be fitted with the cluster bootstrap. This should either be a formula (or be able to be interpreted as one) or a |
data |
dataframe that contains the data. |
clusterid |
variable in data that identifies the clusters. |
family |
error distribution to be used in the model, e.g. |
B |
number of bootstrap samples. |
confint.level |
level of confidence interval. |
n.cores |
number of CPU cores to be used. |
Some useful methods for the obtained clusbootglm
class object are summary.clusbootglm
,
coef.clusbootglm
, and clusbootsample
.
clusbootglm
produces an object of class "clusbootglm"
, containing the following relevant components:
coefficients |
A matrix of |
bootstrap.matrix |
n*B matrix, of which each column represents a bootstrap sample; each value in a column represents
a unit of |
lm.coefs |
Parameter estimates from a single (generalized) linear model. |
boot.coefs |
Mean values of the paramater estimates, derived from the bootstrap coefficients. |
boot.sds |
Standard deviations of cluster bootstrap parameter estimates. |
ci.level |
User defined confidence interval level. |
percentile.interval |
Confidence interval based on percentiles, given the user defined confidence interval level. |
parametric.interval |
Confidence interval based on |
BCa.interval |
Confidence interval based on percentiles with bias correction and acceleration, given the user defined confidence interval level. |
samples.with.NA.coef |
Cluster bootstrap sample numbers with at least one coefficient being |
failed.bootstrap.samples |
For each of the coefficients, the number of failed bootstrap samples are given. |
Mathijs Deen, Mark de Rooij
## Not run: data(opposites) clusbootglm(SCORE~Time*COG,data=opposites,clusterid=Subject) ## End(Not run)