Author: Chun-Sheng Liang <liangchunsheng@lzu.edu.cn>, Hao Wu, Hai-Yan Li, Qiang Zhang, Zhanqing Li, Ke-Bin He, Lanzhou University, Tsinghua University
These data preprocessing methods are developed based on the principles of completeness, accuracy, threshold method, and linear interpolation and through the setting of constraint conditions, time completion & recovery, and fast & efficient calculation and grouping.
Auto-identification of consecutive NA via run-length based grouping is used in observation deletion, outlier removal, and NA interpolation;
Imports: ggplot2, scales, foreach, doParallel, dplyr, reshape2,

Title: Data Quality in Epidemiological Research
c(person(given = "University Medicine Greifswald",
Description: Data quality assessments guided by a
'data quality framework introduced by Schmidt and colleagues 2021'
data quality dimensions integrity, completeness, consistency, and
accuracy. The scope of applicable functions rests on the
availability of extensive metadata which can be provided in
spreadsheet tables. Either standardized (e.g. as 'html5' reports) or
individually tailored reports can be generated. For an introduction
into the specification of corresponding metadata, please refer to the
Imports: patchwork, dplyr (>= 1.0.2), emmeans, ggplot2 (>= 2.1.0),
ggpubr, lme4, lubridate, MASS, MultinomialCI, parallelMap,
R.devices, reshape, rlang, robustbase, utils
Suggests: cowplot (>= 0.9.4), anytime, digest, DT (>= 0.15),
flexdashboard, htmltools, knitr, rmarkdown, rstudioapi,
testthat (>= 2.3.2), tibble, markdown, vdiffr, parallel
Packaged: 2022-08-31 13:13:44 UTC; struckmanns
Author: University Medicine Greifswald [cph],

person(given = "German Research Foundation (DFG SCHM 2744/3-1)",
person(given = "European Union’s Horizon 2020 programme (euCanSHare, grant agreement No. 825903)",
'data quality framework introduced by Schmidt and colleagues, 2021'
Stephan Struckmann [aut, cre] (<https://orcid.org/0000-0002-8565-7962>),
German Research Foundation (DFG SCHM 2744/3-1) [fnd],
European Union’s Horizon 2020 programme (euCanSHare, grant agreement