simulation: Simulate a dataset which can be analyzed by SLTCA
In tengfei-emory/SLTCA: SLTCA: Scalable and Robust Latent Trajectory Class Analysis Using Artificial Likelihood
Description
Usage
Arguments
Value
Author(s)
Examples
Description
Simulate a dataset with longitudinal observations.
Usage
1
simulation(n)
Arguments
n
Sample size.
Value
Returns a data frame with 6 longitudinal features y.1 - y.6, including count (y.1 and y.2), binary (y.3 and y.4) and continuous (y.5 and y.6) type. Variable baselinecov is the baseline risk factor of latent classes. Variable latent is the true latent class labels.
Author(s)
Teng Fei. Email: tfei@emory.edu
Examples
1
dat <- simulation(500)
tengfei-emory/SLTCA documentation built on Oct. 5, 2020, 12:15 a.m.
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Description Usage Arguments Value Author(s) Examples
Description
Simulate a dataset with longitudinal observations.
Usage
1 | simulation(n)
|
Arguments
n |
Sample size. |
Value
Returns a data frame with 6 longitudinal features y.1 - y.6, including count (y.1 and y.2), binary (y.3 and y.4) and continuous (y.5 and y.6) type. Variable baselinecov is the baseline risk factor of latent classes. Variable latent is the true latent class labels.
Author(s)
Teng Fei. Email: tfei@emory.edu
Examples
1 | dat <- simulation(500)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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