Description Usage Arguments Examples
This function calculates the Generalized Method of Moments (GMM) parameter estimates and standard errors for longitudinal proportion (0,1) responses. This is modeled similarly to a Beta Regression using a logit link. The function allows for unbalanced data, meaning subjects can have different numbers of times of observation. Both time-independent covariates and time-dependent covariates can be accommodated. Time-dependent covariates can be handled either by specifying the type of each time-dependent covariate, or by allowing the data to determine appropriate moment conditions through the extended classification method.
1 2 | TSGMM_Beta(yvec, subjectID, Zmat, Xmat, Tvec, N, mc = "EC",
covTypeVec = c(-1))
|
yvec |
The vector of responses, ordered by subject, time within subject. |
subjectID |
The vector of subject ID values for each response. |
Zmat |
The design matrix for time-independent covariates. |
Xmat |
The design matrix for time-dependent covariates. |
Tvec |
The vector of times for each subject. |
N |
The number of subjects. |
mc |
The method of identifying appropriate moment conditions, either 'EC' for extended classification (default) or 'Types' for user-identified types. |
covTypeVec |
The vector indicating the type of each time-dependent covariate, according to the order of the columns of Xmat. |
1 |
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