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                <h3><span class="mw-headline" id="Design"><i class="fa fa-sitemap"></i> Research Design</span></h3>
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                            <li>[[Experimental Methods]]</li>
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                            <li>[[Quasi-Experimental Methods]]</li>
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                            <li>[[Research Ethics]]</li>
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                            <li>[[Sampling & Power Calculations]]</li>
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                <h3><span class="mw-headline" id="Data"><i class="fa fa-database"></i> Data Collection</span></h3>
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                            <li>[[Primary Data Collection]]</li>
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                            <li>[[Secondary Data Sources]]</li>
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                            <li>[[Field Management]]</li>
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                            <li>[[Questionnaire Design]]</li>
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                <h3><span class="mw-headline" id="Analysis"><i class="fa fa-search"></i> Analysis</span></h3>
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                            <li>[[Data Management]]</li>
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                            <li>[[Data Cleaning]]</li>
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                            <li>[[Data Analysis]]</li>
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                            <li>[[Software Tools]]</li>
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                <h3><span class="mw-headline" id="Fieldwork"><i class="fa fa-globe"></i> Publication</span></h3>
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                            <li>[[Reproducible Research]]</li>
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                            <li>[[Publishing Data]]</li>
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                            <li>[[Collaboration Tools]]</li>
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                            <li>[[Dissemination]]</li>
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'''Welcome to the DIME Wiki!'''
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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.
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            <h3 class="mega_title"><span class="mw-headline" id="Recent_Contributions"><b>Cross-cutting Resources</b></span></h3>
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                            <div class="rec_title">[[Stata Coding Practices]]</div>
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                            <div class="rec_title">[[SurveyCTO Coding Practices]]</div>
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                            <div class="rec_title">[[Check Lists]]</div>
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<h3 class="mega_title"><span class="mw-headline" id="Recent_Contributions"><b>Download the Dime Analytics Data Handbook </b></span></h3>
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[[File:BookBanner.png|700px||center|link=https://worldbank.github.io/dime-data-handbook/]]
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= Chapter 1: Data Work Management =
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                        <h3 class="mega_title text-center"><b>Manifesto</b></h3>
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The '''DIME Wiki''' is a public good developed and maintained by [https://www.worldbank.org/en/research/dime/data-and-analytics DIME Analytics], a team which creates tools that improve the quality of impact evaluation research at [https://www.worldbank.org/en/research/dime DIME]. The DIME Wiki is targeted to all researchers and M&E specialists at the World Bank, clients who are managing data collection efforts in the field, donor institutions, universities, NGOs, and governments. </onlyinclude>While there are many existing impact evaluation resources, none meet the specific gap the DIME Wiki aims to fulfill: a resource focused on practical implementation guidelines rather than theory, open to the public, easily searchable, suitable for users of varying levels of expertise, up-to-date with the latest technological advances in electronic data collection, with a vibrant network of editors who are experts in this field.
  
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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
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'''DIME''' is the impact evaluation unit of the World Bank's Development Research Group. Part of DIME’s mission is to intensify the production of, and access to, public goods that improve the quantity and quality of global development research, while lowering the costs of performing impact evaluations for the entire research community. The DIME Wiki aims to further this initiative, and is funded by the United Kingdom’s Foreign, Commonwealth & Development Office through the i2i Trust Fund.
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== Project Folder Management ==
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We have a standardized folder structure that we want all DIME projects to follow.
 
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== Stata Programming ==
 
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Best practices and style guides
 
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== Questionnaire Programming ==
 
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Best practices and style guides for SurveyCTO
 
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=  Chapter 2: Data Sources =
 
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This chapter deals with the types of data sources we work with at DIME and the best practices associated with each of them
 
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== Household Surveys ==
 
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Everything from survey management, questionnaire development, to processes for data quality assurance
 
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== New Sources of Data ==
 
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Big data, geo data etc. What have we done and what resources do we have?
 
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== Admin Data and other data collected by others ==
 
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Best practices for integrating data not collected by us
 
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=  Chapter 3: Data Curation - From Raw Data to Final Outputs =
 
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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.
 
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== Data Import  ==
 
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Import from different raw formats to Stata's .dta format.
 
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== Data Validation and Cleaning ==
 
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Data validation and cleaning goes hand in hand. Use your critical thinking when validating the data
 
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== Constricting variables and data sets for Analysis ==
 
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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.
 
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== Data Analysis and Presentation of Results ==
 
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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.
 

Latest revision as of 21:36, 15 September 2020


Cross-cutting Resources

Stata Coding Practices
SurveyCTO Coding Practices
Check Lists


Download the Dime Analytics Data Handbook

BookBanner.png

Manifesto

The DIME Wiki is a public good developed and maintained by DIME Analytics, a team which creates tools that improve the quality of impact evaluation research at DIME. The DIME Wiki is targeted to all researchers and M&E specialists at the World Bank, clients who are managing data collection efforts in the field, donor institutions, universities, NGOs, and governments. While there are many existing impact evaluation resources, none meet the specific gap the DIME Wiki aims to fulfill: a resource focused on practical implementation guidelines rather than theory, open to the public, easily searchable, suitable for users of varying levels of expertise, up-to-date with the latest technological advances in electronic data collection, with a vibrant network of editors who are experts in this field.

DIME is the impact evaluation unit of the World Bank's Development Research Group. Part of DIME’s mission is to intensify the production of, and access to, public goods that improve the quantity and quality of global development research, while lowering the costs of performing impact evaluations for the entire research community. The DIME Wiki aims to further this initiative, and is funded by the United Kingdom’s Foreign, Commonwealth & Development Office through the i2i Trust Fund.

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