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'''Welcome to the DIME Wiki!'''  
'''Welcome to the DIME Wiki!'''  


We have organized the Wiki in Chapters. Each chapter has a few high level topics. All pages on this Wiki is organized into one of those high level topics. It is always good to start by reading the page associated with the high level task.
See below for the topics/stubs/chapters of the wiki


= Chapter 0: How to contribute to the Wiki =
= Chapter 0: How to contribute to the Wiki =
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Everyone is encouraged to contribute to this Wiki. We reserve the right to review edits. For instructions on how to contribute to the Wiki click [[DIME Wiki Contributions|here]].  
Everyone is encouraged to contribute to this Wiki. We reserve the right to review edits. For instructions on how to contribute to the Wiki click [[DIME Wiki Contributions|here]].  


= Chapter 1: Data Work Management =
= Chapter 1: Work Cycle topics/stubs/chapters =


This chapter relates to general skills in relation to data work, such as how to you organize you data folder so that all members of your team can collaborate on the data work. It also includes
#[[Impact Evaluation Design]]
#[[Sampling]]
#[[Preparing for Data Collection]]
#[[Questionnaire Design]]
#[[Questionnaire Programming]]
#[[Survey firm procurement]]
#[[Questionnaire pilot]]
#[[Enumerator training]]
#[[Planning field work]]
#[[Monitoring data quality]]
#[[Data management]]
#[[Data cleaning]]
#[[Data analysis]]
#[[Reproducible Research]]


== Project Folder Management ==
= Chapter 2: Stand alone topics/stubs/chapter =


We have a standardized folder structure that we want all DIME projects to follow.
#[[Stata coding practices]]
 
#[[SurveyCTO coding practices]]
== Stata Programming ==
#[[Geo spatial data]]
 
Best practices and style guides
 
== Questionnaire Programming ==
 
Best practices and style guides for SurveyCTO
 
=  Chapter 2: Data Sources =
 
This chapter deals with the types of data sources we work with at DIME and the best practices associated with each of them
 
== Household Surveys ==
 
Everything from survey management, questionnaire development, to processes for data quality assurance
 
== New Sources of Data ==
 
Big data, geo data etc. What have we done and what resources do we have?
 
== Admin Data and other data collected by others ==
 
Best practices for integrating data not collected by us
 
=  Chapter 3: Data Curation - From Raw Data to Final Outputs =
 
This chapter deals with each stage of the data work of a typical impact evaluation. While this chapter takes the perspective of the a SurveyCTO/Stata environment, much of what is written here is still useful if you are using other tools for your data work.
 
== Data Import  ==
 
Import from different raw formats to Stata's .dta format.
 
== Data Validation and Cleaning ==
 
Data validation and cleaning goes hand in hand. Use your critical thinking when validating the data
 
== Constricting variables and data sets for Analysis ==
 
After cleaning we need to construct the averages, aggregates, ratios, categories etc. that we will use in analysis. We also need to creaet the data sets needed such as panel data sets from multiple rounds of data.
 
== Data Analysis and Presentation of Results ==
 
General advice for analysis and outputting the results. The purpose of this topic is not give you any advise on how to analyse your data, but to give advise on how to implement your analysis after you have made a plan for how to analyse your data.

Revision as of 22:16, 13 December 2016

DIMEi2i.JPG

Welcome to the DIME Wiki!

See below for the topics/stubs/chapters of the wiki

Chapter 0: How to contribute to the Wiki

Everyone is encouraged to contribute to this Wiki. We reserve the right to review edits. For instructions on how to contribute to the Wiki click here.

Chapter 1: Work Cycle topics/stubs/chapters

  1. Impact Evaluation Design
  2. Sampling
  3. Preparing for Data Collection
  4. Questionnaire Design
  5. Questionnaire Programming
  6. Survey firm procurement
  7. Questionnaire pilot
  8. Enumerator training
  9. Planning field work
  10. Monitoring data quality
  11. Data management
  12. Data cleaning
  13. Data analysis
  14. Reproducible Research

Chapter 2: Stand alone topics/stubs/chapter

  1. Stata coding practices
  2. SurveyCTO coding practices
  3. Geo spatial data
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