Useful functions for various DDI (Data Documentation Initiative) related inputs and outputs.

admisc (>= 0.4), haven, readr, tibble, xml2

admisc (>= 0.12), haven, readr, tibble, tools, xml2

admisc (>= 0.16), readr, declared, haven, tools, xml2, readxl,
writexl

admisc (>= 0.17), readr, declared (>= 0.6), haven, tools,
xml2, readxl, writexl

admisc (> 0.17), readr, declared (> 0.6), haven, tools, xml2,
readxl, writexl

admisc (> 0.19), readr, declared (> 0.6), haven, tools, xml2,
readxl, writexl

c(
person("Domagoj", "Ćevid", email = "cevid@stat.math.ethz.ch", role = c("aut")),
person("Chengzhu", "Huang", email="czhuang0710@gmail.com", role = c("aut")),
person("Zijian", "Guo", email = "zijguo@stat.rutgers.edu", role = c("aut","cre")),
person("Peter", "Bühlmann", email = "buhlmann@stat.math.ethz.ch", role = c("aut")))
Statistical inference for the regression coefficients in high-dimensional linear models with hidden confounders. The Doubly Debiased Lasso method was proposed in <arXiv:2004.03758>.
Domagoj Ćevid [aut],
Chengzhu Huang [aut],
Zijian Guo [aut, cre],
Peter Bühlmann [aut]

Tim Riffe, Everton Lima, Bernardo Queiroz
A set of three two-census methods to the estimate the degree of death registration coverage for a population. Implemented methods include the Generalized Growth Balance method (GGB), the Synthetic Extinct Generation method (SEG), and a hybrid of the two, GGB-SEG. Each method offers automatic estimation, but users may also specify exact parameters or use a graphical interface to guess parameters in the traditional way if desired.

William Hua <whua4@jhu.edu>, Yanxun Xu <yanxun.xu@jhu.edu>
A nonparametric Bayesian approach to survival analysis. The functions perform inference via MCMC simulations from the posterior distributions for a Dependent Dirichlet Process-Gaussian Process prior. To maximize computational efficiency, some of the computations are performed in 'Rcpp'.
Rcpp (>= 0.12.11), MASS, survival, mc2d, mvnfast

Disease-Related Differential Proteins and Co-Expression Network
Analysis
Functions designed to connect disease-related differential proteins and
co-expression network. It provides the basic statics analysis included t test, ANOVA analysis.
The network construction is not offered by the package, you can used 'WGCNA' package which you
can learn in Peter et al. (2008) <doi:10.1186/1471-2105-9-559>. It also provides module analysis
included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and
hub analysis.
stats, ggplot2, ggalt, MEGENA, igraph, Hmisc, utils,
grDevices, plyr, scales, grid, VennDiagram