ordCWGEE | R Documentation |
Solves the cluster-weighted generalized estimating equations for correlated ordinal responses in clustered longitudinal data assuming a cumulative link logit model for the marginal probabilities using the method of quasi-least squares.
ordCWGEE(formula, data, id, cluster.var, time.var, time.str)
formula |
a formula expression as for other regression models. |
data |
an optional data frame containing the variables provided in
|
id |
a vector that identifies the clusters. |
cluster.var |
a vector that identifies the unit within a cluster. |
time.var |
a vector that identifies the repeated observation of a unit. |
time.str |
a character string that indicates the temporal working correlation structure.
Options include |
The data
must be provided in case level or equivalently in ‘long’ format.
Returns an object of the class "cwgee"
. This has components:
call |
the matched call. |
coefficients |
the estimated regression parameter vector of the marginal model. |
coef.names |
the variable name of the coefficients. |
robust.variance |
the estimated "robust" covariance matrix. |
robust.se |
the estimated "robust" standard errors. |
wald.chisq |
the Wald Chi-square test statistic for coefficient estimates. |
p.value |
the p-value based on a Wald Chi-square test statistic that no covariates are statistically significant. |
alpha |
the estimated temporal correlation coefficient. |
niter |
the number of iterations the model took to converge. |
time.str |
the temporal working correlation structure assumed for the model. |
Aya Mitani
data(perio)
fitmod <- ordCWGEE(formula = cal ~ mets + edu + age + smoking, data = perio,
id = subject, cluster.var = tooth, time.var = visit, time.str = "ind")
summary(fitmod)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.