In nskourlis/MSMplus: Prepare MSMplus input files and locally deploys the MSMplus app

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MSMplus

MSMplus is a useful tool for presentation of results from a multi-state analysis in an easy, comprehensible and meaningful way. It aids the user to present research findings to targeted audiences.

However, the results need to be provided to the app either as a csv/excel or a json file of specific structure.

The advisable approach is the manual creation of an excel/csv file with the analysis results by the researcher according to certain formatting and naming rules described in this tutorial.

Here is an example data file structure:

#load("excel_input_file_ex.rda", envir = parent.frame(), verbose = FALSE)

#excel_input_file_ex[104:106,1:15]

We have created an alternative way for deriving the MSMplus input files to avoid the labour. The json files can be easily derived while running the multi-state models. In Stata, this is done via the commands msboxes and predictms.

In R the input files can be generated via the current package and the use of its funtions: flexjson, msmjson, mstatejson. That being said we still advise for the manual approach as the researcher does not need to have any knowledge of R or Stata, as the analysis can be conducted via any statistical software.

The user can locally launch the MSMplus application by writting MSMplus_prepare::runMSMplus() or access it online at https://nskbiostatistics.shinyapps.io/MSMplus/

Installation

You can install the development version of MSMplus from GitHub with:

# install.packages("devtools")
devtools::install_github("nskourlis/MSMplus")

Example

This is a basic example which shows you how to launch MSMplus:

library(MSMplus)
#runMSMplus()

Read the vignette to see how to automatically produce the input files for MSMplus

nskourlis/MSMplus documentation built on Dec. 7, 2023, 4:53 a.m.