DeclareDesign

Declare and Diagnose Research Designs

Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.

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Description file content

Package
DeclareDesign
Title
Declare and Diagnose Research Designs
Version
0.10.0
Description
Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
Depends
R (>= 3.4.0), randomizr (>= 0.16.1), fabricatr (>= 0.4.0), estimatr (>= 0.10.0)
Imports
rlang, methods
License
MIT + file LICENSE
URL
BugReports
https://github.com/DeclareDesign/DeclareDesign/issues
Encoding
UTF-8
LazyData
true
RoxygenNote
6.0.1
Suggests
testthat, knitr, rmarkdown, AER, dplyr, data.table, ggplot2, future.apply, broom, MASS, Matching, betareg, biglm, gam, lfe, sf, reshape2
VignetteBuilder
knitr
NeedsCompilation
no
Packaged
2018-07-23 18:12:40 UTC; gdblair
Author
Graeme Blair [aut, cre], Jasper Cooper [aut], Alexander Coppock [aut], Macartan Humphreys [aut], Neal Fultz [aut]
Maintainer
Graeme Blair
Repository
CRAN
Date/Publication
2018-07-29 21:50:03 UTC

install.packages('DeclareDesign')

0.10.0

18 days ago

https://declaredesign.org

Graeme Blair

MIT + file LICENSE

Depends on

R (>= 3.4.0), randomizr (>= 0.16.1), fabricatr (>= 0.4.0), estimatr (>= 0.10.0)

Imports

rlang, methods

Suggests

testthat, knitr, rmarkdown, AER, dplyr, data.table, ggplot2, future.apply, broom, MASS, Matching, betareg, biglm, gam, lfe, sf, reshape2

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