Title: | Fits Conditional Generalized Linear Models |
---|---|
Description: | Estimates the ratio of the regression coefficients and the dispersion parameter in conditional generalized linear models for clustered data. |
Authors: | Arvid Sjolander |
Maintainer: | Arvid Sjolander <[email protected]> |
License: | GPL (>= 2) |
Version: | 1.1 |
Built: | 2024-11-26 06:25:36 UTC |
Source: | CRAN |
cglm
estimates the ratio of the regression coefficients and the
dispersion parameter in conditional generalized linear models. This
is of particular interest in the so-called case-time-control design.
cglm(method, formula, data, id, link, ...)
cglm(method, formula, data, id, link, ...)
method |
a string specifying the desired estimation method; either |
formula |
a symbolic description of the model to be fitted. |
data |
a data frame containing the variables in the model. |
id |
a string containing the name of the cluster identification variable. |
link |
a string specifying the desired link function. This argument is not used
when |
... |
optional arguments passed on to the |
Let and
be the outcome and covariate(s) for subject
in cluster
, respectively. Consider the conditional generalized
linear model
where
cglm
estimates the ratio
This ratio is of particular interest in so-called case-time-control designs; see Sjolander (2016) and Sjolander and Ning (2018) for details. Two estimation methods are allowed; the two-step method proposed by Sjolander (2016) and the conditional maximum likelihood method proposed by Sjolander and Ning (2018).
An object of class "cglm"
is a list containing
call |
the matched call. |
coefficients |
the ratio of the estimated coefficients and the estimated dispersion parameter. |
var |
the variance-covariance matrix. |
convergence |
was a solution found to the estimating equations? |
Missing data are not allowed.
Arvid Sjolander.
Sjolander A. (2017). The case-time-control method for non-binary exposures. Sociological Methodology 47(1), 182-211.
Sjolander A., Ning Y. (2018). A general and robust estimation method for the case-time-control design. Sociological Methodology 49(1), 349-365.
data(teenpov) fit.ide <- cglm(method="ts", formula=hours~nonpov+inschool+spouse+age+mother, data=teenpov, id="ID", link="identity") summary(fit.ide) fit.log <- cglm(method="ts", formula=hours~nonpov+inschool+spouse+age+mother, data=teenpov, id="ID", link="log") summary(fit.log) fit.cglm <- cglm(method="cml", formula=hours~nonpov+inschool+spouse+age+mother, data=teenpov, id="ID") summary(fit.cglm)
data(teenpov) fit.ide <- cglm(method="ts", formula=hours~nonpov+inschool+spouse+age+mother, data=teenpov, id="ID", link="identity") summary(fit.ide) fit.log <- cglm(method="ts", formula=hours~nonpov+inschool+spouse+age+mother, data=teenpov, id="ID", link="log") summary(fit.log) fit.cglm <- cglm(method="cml", formula=hours~nonpov+inschool+spouse+age+mother, data=teenpov, id="ID") summary(fit.cglm)
This is a print
method for class "summary.cglm"
.
## S3 method for class 'summary.cglm' print(x, digits=max(3L, getOption("digits")-3L), signif.stars=getOption("show.signif.stars"), ...)
## S3 method for class 'summary.cglm' print(x, digits=max(3L, getOption("digits")-3L), signif.stars=getOption("show.signif.stars"), ...)
x |
an object of class |
digits |
the number of significant digits to use. |
signif.stars |
logical. If TRUE, "significance stars" are printed for each coefficient. |
... |
not used. |
Arvid Sjolander
##See documentation for cglm.
##See documentation for cglm.
This is a summary
method for class "cglm"
.
## S3 method for class 'cglm' summary(object, ...)
## S3 method for class 'cglm' summary(object, ...)
object |
an object of class |
... |
not used. |
Arvid Sjolander
##See documentation for cglm.
##See documentation for cglm.
This dataset is a subset of a dataset described by Allison (2009). The original data by Allison (2009) comes from the National Longitudinal Survey of Youth (NLSY), and contains information on 1151 teenage girls who were interviewed annually for five years, starting in 1979. The teenpov dataset is constructed by first identifying, for each girl, the first interview at which the girl is not in poverty, then excluding all subsequent interviews for that girl. After this exclusion, the dataset contains 1342 interviews from 401 girls. This procedure is described in greater detail by Sjolander (2017).
data(teenpov)
data(teenpov)
The dataset contains the following variables:
a unique subject-identifier.
1 if the girl is currenlty not in poverty according to U.S. federal standards.
the number of hours that the girl currently works per week.
1 if the girl is currently enrolled in school, 0 otherwise.
1 if the girl is currently living with a spouse, 0 otherwise.
the girl's current age.
1 if the girl currently has at least 1 child, 0 otherwise.
Allison P. (2009). Fixed effects regression models: quantitative applications in the Social sciences. Thousand Oaks, CA: Sage.
Sjolander A. (2017). The case-time-control method for non-binary exposures. Sociological Methodology 47(1), 182-211.