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SequentialDesign  

Observational Database Study Planning using Exact Sequential Analysis for Poisson and Binomial Data
View on CRAN: Click here


Download and install SequentialDesign package within the R console
Install from CRAN:
install.packages("SequentialDesign")

Install from Github:
library("remotes")
install_github("cran/SequentialDesign")

Install by package version:
library("remotes")
install_version("SequentialDesign", "1.0")



Attach the package and use:
library("SequentialDesign")
Maintained by
Judith Maro
[Scholar Profile | Author Map]
First Published: 2017-11-16
Latest Update: 2017-11-16
Description:
Functions to be used in conjunction with the 'Sequential' package that allows for planning of observational database studies that will be analyzed with exact sequential analysis. This package supports Poisson- and binomial-based data. The primary function, seq_wrapper(...), accepts parameters for simulation of a simple exposure pattern and for the 'Sequential' package setup and analysis functions. The exposure matrix is used to simulate the true and false positive and negative populations (Green (1983) , Brenner (1993) ). Functions are then run from the 'Sequential' package on these populations, which allows for the exploration of outcome misclassification in data.
How to cite:
Judith Maro (2017). SequentialDesign: Observational Database Study Planning using Exact Sequential Analysis for Poisson and Binomial Data. R package version 1.0, https://cran.r-project.org/web/packages/SequentialDesign. Accessed 18 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited SequentialDesign R package
View SequentialDesign citation profile
Other R packages that SequentialDesign depends, imports, suggests or enhances
Complete documentation for SequentialDesign
Functions, R codes and Examples using the SequentialDesign R package
Some associated functions: SCRI.seq . create.exposure . fun.decum . fun.exposure . initialize.data . seq_wrapper . sim.exposure . 
Some associated R codes: fun.decum.R . fun.exposure.R .  Full SequentialDesign package functions and examples
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