mkmiecik14 / mmh

Code for data processing and analysis of the Multimodal Hypersensitivity project

mmh

Code for data processing and analysis of the Multimodal Hypersensitivity project.

More details of this project and data can be found on Open Science Framework (DOI: 10.17605/OSF.IO/27KY9).

Packages, functions, and variables that were used across several scripts are located in r-prep.R

Data were processed and analyzed in the following stages:

Stage 1

Raw data were first preprocessed using the following scripts:

• sscodes-prepro.R - prepared master list of participant id numbers
• avisit-1-prepro.R - prepared assessment visit 1 data exported from REDCap
• ppt-prepro.R - prepared data from quantitative sensory testing (PPT, CPM, TS)
• auditory-eprime-prepro.R - prepared the auditory stimulation task data (behavioral)
• visual-eprime-prepro.R - prepared the visual stimulation task data (behavioral)
• screenvisit-prepo.R - prepared data from screen visit

Stage 2

After preprocessing, data were examined and explored for outliers and trends in the following scripts:

• avisit-1-explore.R - explored REDCap data from assessment 1
• ppt-explore.R - explored QST data
• vis-aud-explore.R- explored the visual and auditory tasks
• extradata-explore.R - explored questionnaire data not included in PCA

Stage 3

Data were prepared for PCA analysis by ensuring equivalent size of the dataframes and converting to wide format in the pca-data-prep.R script. Extra data used for coloring was visualized, prepared, and saved out in extradata-explore.R.

To "refresh" the data for PCA analysis, run the data-refresh.R script to compute stage 1 and stage 3 in one go. (This will not refresh "extra data").

Stage 4

Principal component analysis and inferential testing was performed using the pca-proc.R script.

Stage 5

Annual data for the ICSI (our CPP outcome measure) were pulled from Redcap using the API (api-calls.R) and preprocessed using api-prepro.R. As more participants complete their annual questionnaires, these data can be refreshed by running api-calls.R.

Later longitudinal analyses were completed using api-icsiplus-prepro.R and api-icsiplus-explore.R where pelvic pain outcome was more comprehensively modeled.

Sensory analyses were conducted in sensory-analysis.R and sensory-analysis-explore.R. Sensitivity analyses were conducted in sensitivity-analyses-proc.R.

MISC

Annual questionnaires are processed in annuals.R for a grant prep submission.