Information Decomposition of Two-phase Experiments

Information Decomposition of Two-Phase Experiments
c(person("Kevin", "Chang", email = "k.chang@auckland.ac.nz", role = c("aut", "cre")))
The main purpose of this package is to generate the structure of the analysis of variance
(ANOVA) table of the two-phase experiments. The user only need to input the design and the
relationships of the random and fixed factors using the Wilkinson-Rogers' syntax,
this package can then quickly generate the structure of the ANOVA table with the
coefficients of the variance components for the expected mean squares.
Thus, the balanced incomplete block design and provides the efficiency
factors of the fixed effects can also be studied and compared much easily.

c(person("Kevin", "Chang", email = "k.chang@auckland.ac.nz", role = c("aut", "cre")),
person("Katya", "Ruggiero", email = "k.ruggiero@auckland.ac.nz", role = c("aut")))
Kevin Chang [aut, cre],
Katya Ruggiero [aut]

An R wrapper for the infochimps.com API services
This package provides functions to access all of the APIs
currently available infochimps.com.  For more information see
http://api.infochimps.com/.

Sequence Statistics for Relational Event Models
Aids in creating sequence statistics for Butts's 'relevent' software.

informR: R Tools for Creating Sequence Statistics
Tools for creating sequence statistics, especially for
Butts's egocentric relational event model fitting software in
the relevent R package

Tools for creating sequence statistics, especially for Butts's egocentric relational event model fitting software in the relevent R package

R Tools for Creating Sequence Statistics

Sensitivity Analysis Informed by a Test for Bias
After testing for biased treatment assignment in an observational study using an unaffected outcome, the sensitivity analysis is constrained to be compatible with that test.  The package uses the optimization software gurobi obtainable from <https://www.gurobi.com/>, together with its associated R package, also called gurobi; see: <https://www.gurobi.com/documentation/7.0/refman/installing_the_r_package.html>.  The method is a substantial computational and practical enhancement of a concept introduced in Rosenbaum (1992) Detecting bias with confidence in observational studies Biometrika, 79(2), 367-374  <doi:10.1093/biomet/79.2.367>.