#04.Data collection - sporedata/researchdesigneR GitHub Wiki

Categories for data collection

04.Data collection01.Chatbot
04.Data collection02.Interviews-and-focus-groups
04.Data collection03.Mechanical-Turk
04.Data collection04.Email-surveys
04.Data collection05.Registry
04.Data collection06.Trial
04.Data collection07.Patient-data-donation
04.Data collection08.Platform-trials
04.Data collection09.Data-quality-control
04.Data collection10.Design-and-data-coordination-center
04.Data-collection11.Sampling

In this section, we split data collection from analysis methods. These topics are often mixed, randomized trials being an example where the randomization is discussed along with the corresponding analytical methods. We took a different approach since analytical and data collection methods often have a "many to many" relationship, making it simpler to just split them up.

1. Use cases: In which situations should I use this method?

Prospective data collection should be used in any situation where retrospective data might not be available or when its quality may not be adequate for the project at hand.

2. Input: What kind of data does the method require?

Prospective data collection requires submission and subsequent approval of the protocol and informed consent to an institutional review board, and financial resources to subsidize the data collection process.

3. Algorithm: How does the method work?

Model mechanics

Describing in images

Data science packages

Suggested companion methods

Prospective data collection is often accompanied by the use of pre-existing data such as electronic health records. In addition, patient-centered protocols should be used to involve patients and other stakeholders in all phases of the research project. These include overall design, data collection, interpretation of results, and dissemination of research findings to a wide range of stakeholders.