1. Aggregate Data Research Methods

2. Collecting and Preparing Quantitative Data Where does a researcher find data for analysis and interpretation? Existing data collection or archives Original collection of data and archive for use by other researchers Aggregate data or individual-level data

3. Coding Scheme Monday: Determine the coding procedure and detailed codebook Coding: assigning of numerical values to observations Preserve level of measurement Mutually exclusive & Exhaustive Allow sensible comparisons for theory Parsimony & Detail Account for Missing Data

4. Maintaining a Coding Scheme Codebook – study and data collection description; location (of data), variable, values, codes (include description, source, survey question, etc. as appropriate) Codebook created prior to coding and (perhaps) revised as necessary for consistent coding Verification of coding (intercoder reliability) as well as data entry for coding reliability Processing error increases for vague instructions, open-ended questions or non-structured material, lack of coder interaction

5. Coding Devices Coding Sheets (transfer sheets) Edge coding Optical scanning Direct data entry

9. Best Coding/Entry Practices Data editing and codebook revision Double coders a/o Double entry (and resolution of inconsistencies) Data cleaning wild or illegitimate codes filter or contingency questions

10. Six Stages of the Research Process Formulation of Theory Operationalization of Theory Selection of Appropriate Research Techniques Observation of Behavior (Data Collection) Analysis of Data Interpretation of Results

11. Reporting Results: Writing and Evaluating Reports Title Abstract Introduction Methods Findings Conclusion

12. Tips on Style Work from an outline Be simple (parsimonious) and precise Use words and phrases you know Revise, revise, revise (reread, revise, rewrite) Seek others opinions Do not overstate a point Distinguish observation and opinion Use proper citation & documentation of sources

13. Critical Reading: Is there… Clearly specified research question? Demonstrated value and significance? Clear concepts? Clear explanations? Identified dependent and independent variables? Hypothesis(ses) empirical, general, & plausible Valid and reliable measures? Specified unit of analysis and observations? Identified sample selection problems? Good checklist (pp.384-385)

14. Aggregate Data Categories of aggregate indicators Summative indicatorsAdditive group characteristics Syntality indictorsGroup or system characteristics Types of groups Geographic groups Demographic groups

15. Six Types (and Sources) of Aggregate Data Census data (US and other) Organizational data (government and private) Sample surveys Publications content Event data Judgmental data

16. Challenges for Data Collection and Manipulation Variable precision Standardization Data transformation Index construction Ecological fallacy Reduction or Individualistic Fallacy