Package 'blindreview'

Title: Enables Blind Review of Database
Description: Randomly reassigns the group identifications to one of the variables of the database, say Treatment, and randomly reassigns the observation numbers of the dataset. Reorders the observations according to these new numbers. Centers each group of Treatment at the grand mean in order to further mask the treatment. An unmasking function is provided so that the user can identify the potential outliers in terms of their original values when blinding is no longer needed. It is suggested that a forward search procedure be performed on the masked data. Details of some forward search functions may be found in <https://CRAN.R-project.org/package=forsearch>.
Authors: William Fairweather [aut, cre]
Maintainer: William Fairweather <[email protected]>
License: GPL (>= 3)
Version: 2.0.0
Built: 2024-11-16 05:36:00 UTC
Source: https://github.com/cran/blindreview

Help Index


Enables Blind Review of Database

Description

Assigns identification randomly to one of the variables of the dataset as chosen by the user, say Treatment, and assigns random number to the observations of the dataset. Reorders the observations. A file is created so that the user can identify any outliers identified by the review in terms of their original, unchanged values.

Usage

brMask(data, blinded, verbose=TRUE)

Arguments

data

Database to be evaluated

blinded

Character, name of variable to be blinded

verbose

TRUE causes function identifier to display before and after run

Details

The first variable of the database must be Observation. The first element of the brMask object is the database to be reviewed blindly.

Value

LIST

Masked Dataframe

Database with substitute variable and substitute observation numbers

Randomization Date

Date of randomization of blinded items

Variable

Codes for unblinding variable that was blinded

Observations

Codes for unblinding observation numbers

Call

Call to this function

Author(s)

William R. Fairweather

References

Atkinson, A and M Riani. Robust Diagnostic Regression Analysis, Springer, New York, 2000. Pinheiro, JC and DM Bates. Mixed-Effects Models in S and S-Plus, Springer, New York, 2000. https://CRAN.R-project.org/package=forsearch E9 Statistical Principles for clinical Trials, US Food & Drug Administration and International Conference on Harmonization, 1998

Examples

Observation <- 1:14
Dose <- c(3.4,5.2,7,8.5,10.5,13,18,21,28,6.5,10,14,21.5,29)
Prep <- factor(c(rep(0,9),rep(1,5)))
Convulse <- c(0,5,11,14,18,21,23,30,27,2,10,18,21,27)
Total <- c(33,32,38,37,40,37,31,37,30,40,30,40,35,37)
NoConvulse <- Total-Convulse
mice <- data.frame(Observation,Dose,Prep,Convulse,Total,NoConvulse)
brMask(data=mice,blinded="Prep")

Print Tables of Encoded and Original Variable IDs and Observation Numbers

Description

Prints tables resulting from masking performed by brMask function to permit user to identify potential outliers by their original identities

Usage

unmask(object, obsrange=NULL, verbose=TRUE)

Arguments

object

Name of brMask object

obsrange

NULL or vector of integers, NULL causes entire data frame of observation numbers to be printed

verbose

TRUE causes function identifier to display before and after run

Value

None returned, printout only

Author(s)

William R. Fairweather