knitr, rmarkdown, rpact, mvtnorm, testthat (>= 3.0.0)

Performs power and sample size calculation for non-proportional
hazards model using the Fleming-Harrington family of weighted log-rank tests.
The sequentially calculated log-rank test score statistics are assumed to
have independent increments as characterized in Anastasios A. Tsiatis (1982)
<doi:10.1080/01621459.1982.10477898>. The mean and variance of log-rank test
score statistics are calculated based on Kaifeng Lu (2021)
<doi:10.1002/pst.2069>. The boundary crossing probabilities are calculated
using the recursive integration algorithm described in Christopher Jennison
and Bruce W. Turnbull (2000, ISBN:0849303168).

The basic idea of latent semantic analysis (LSA) is,
that text do have a higher order (=latent semantic) structure which,
however, is obscured by word usage (e.g. through the use of synonyms
or polysemy). By using conceptual indices that are derived statistically
via a truncated singular value decomposition (a two-mode factor analysis)
over a given document-term matrix, this variability problem can be overcome.

The basic idea of latent semantic analysis (LSA) is,
that text do have a higher order (=latent semantic) structure which,
however, is obscured by word usage (e.g., through the use of synonyms
or polysemy). By using conceptual indices that are derived statistically
via a truncated singular value decomposition (a two-mode factor analysis)
over a given document-term matrix, this variability problem can be overcome.

The basic idea of latent semantic analysis (LSA) is, that
text do have a higher order (=latent semantic) structure which,
however, is obscured by word usage (e.g. through the use of
synonyms or polysemy). By using conceptual indices that are
derived statistically via a truncated singular value
decomposition (a two-mode factor analysis) over a given
document-term matrix, this variability problem can be overcome.

c(
person("Tyler", "Matta", email = "tyler.matta@gmail.com", role = c("aut", "cre")),
person("Yuan-Ling Linda", "Liaw", email = "linda08@uw.edu", role = "ctb"),
person("Leslie", "Rutkowski", email = "leslie.rutkowski@cemo.uio.no", role = "ctb"),
person("David", "Rutkowski", email = "david.rutkowski@cemo.uio.no", role = "ctb"),
person("Kondwani Kajera", "Mughogho", email = "k.k.mughogho@cemo.uio.no", role = "ctb")
)
Provides functions to simulate data from large-scale educational
assessments, including background questionnaire data and cognitive item
responses that adhere to a multiple-matrix sampled design.
Tyler Matta [aut, cre],
Yuan-Ling Linda Liaw [ctb],
Leslie Rutkowski [ctb],
David Rutkowski [ctb],
Kondwani Kajera Mughogho [ctb]