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Note: This User story is currently being re-scoped in advance of preparations for the Dagstuhl 2014 sprint.
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There are several related current or proposed use cases that might be incorporated under this User Story - either as use cases of design or execution. These include
| Design | Execution |
|---|---|
| Study Inception | Data collection/Fieldwork |
| Data Management Planning | Data Processing Pipeline |
| Survey Development | Analysis and dissemination |
| Protocol specification |
| Hypothesis generation |
| Sampling, Weighting, ... |
PREVIOUS VERSION:
Full purpose: To provide an understanding of the study design addressing a business case (e.g., research question); to provide information which would allow, for example, (a) a researcher to field or repeat a study, or (b) a statistician to recreate a statistic or finding, or (c) a data user to understand the methods used to collect the data..
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Discussion (Steve, Dan, Simon, Barry, Nicole - Toronto May 2014)
Proposals
Topics in Scope | Definition | Usage/example |
| Study Design | The "how"; specifications for how the research will be carried out and how the data will be obtained, collected, or captured. | |
| Business Case | The "why"; statement of why the research will be conducted and the research question(s) that will be addressed. | |
| Sample Frame | Identification of population upon which the survey will be conducted. | |
| Sampling | Specifying how the sample will be drawn from the frame. | See source link on sampling.
A sampling plan for any statistical activity for Dan Gillman |
| Estimation | Consideration of costs, size, bias, and confidence in the design of the variance estimates. | |
| Weighting | Representative power of each case in a data set and how they will be determined. | See source link on weighting. |
Data editing/transformations | Editing/cleaning or coding during or in context of data collection or administration of instrument (contingent upon mode). | Examples include looking for out-of-bound values, data inconsistencies, reporting errors, recoded variables (variables created from existing values from other variables), or coding open-ended text into categories. |
Imputation/non-response adjustment | Application or not to apply coding or a statistical technique to a dataset to populate missing values. |
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Questionnaire development (logical instrument), mode effects | Creation of question types, response categories and options, skip logic, testing, mode of administration | Design of the data collection instruments and design of methodological tests (focus groups, cognitive interviews) to assist with instrument development. See source link on questionnaire design. |
Incorporating classifications | Specification for how the units will be subdivided in samples, tables or analyses. | Selection of strata, construction of data tables |
Analytic plan | Identification of analytic approach and specific statistical tests and manipulations. |
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Questions
- We need to decide those views that are critical to describing methodology but that are out of scope, such as Logical Instrument, Classifications, etc.
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