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Cut-to-the-Chase Research Making the Most of Available Data

Cut-to-the-Chase Research Making the Most of Available Data. Keith Curry Lance Consultant. Outline. Planning primary data collection Secondary analysis “Research literacy” Types of secondary analysis Issues in using available data Benefits of using available data Caveats.

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Cut-to-the-Chase Research Making the Most of Available Data

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  1. Cut-to-the-Chase ResearchMaking the Most of Available Data Keith Curry Lance Consultant

  2. Outline • Planning primary data collection • Secondary analysis • “Research literacy” • Types of secondary analysis • Issues in using available data • Benefits of using available data • Caveats

  3. Planning primary data collection • Sampling frame for primary data collection • Aid in designing instruments

  4. Sampling frame for primary data collection • Registration files in user/non-user surveys • Federal academic and public library universe data in ALA salary survey

  5. Aid in designing instruments • User and non-user surveys drawing questions from each other • CO PL return-on-investment survey based on FL, MO, and SC examples • Virtue of replication

  6. Secondary analysis • Existing data from single source • Existing data from multiple sources • Existing data combined with primary analysis of original data collection

  7. Existing data from single source • Local LibQual+ data analyses

  8. Existing data from multiple sources • User & library data in planning process • Catalog and circulation records in collection analysis • “CO” studies on impact of school libraries on CSAP scores

  9. Existing data + primary analysis of original data • School library impact studies in states other than CO

  10. “Research Literacy” • Secondary analysis of primary analyses of original data

  11. Secondary analysis of primary analyses of original data • Krashen on the power of reading

  12. Types of secondary analysis • Comparing & contrasting • with ungrouped cases (ranking) • with grouped cases (benchmarking) • with standards, guidelines (testing) • Analyzing trends • Conducting experiments (before & after) • Establishing relationships (correlation)

  13. Issues in Using Existing Data • Accessing existing data • Locating & acquiring data (existing v. available) • Etiquette involved in using existing data • Matching data from different sources • Matching data (mortality & migration) • Obtaining contemporary data • Determining comparability

  14. More Issues • Assessing data quality • Validity • Reliability • Combining & disaggregating data • Combining cases, data • Disaggregating cases, data • Living with data limitations • Quality • Precision • Synchronicity

  15. Still More Issues... • Premeditating existing data & secondary analyses • Ensuring library issues are represented in general surveys • “Piggybacking” on other surveys • Sharing samples with others • Being proactive • Keeping up with the literature & research in progress • Anticipating issues

  16. Benefits of Using Existing Data • Practical • Social • Intellectual

  17. Practical Benefits • Economies of scale (40% of project costs) • Preliminary step to new data collection • Clarifying ideas • Sharpening instruments • Identifying issues deserving special attention

  18. Social Benefits • Spares complicating an issue with new data collection • Overcomes obstacles to new data collection • Democratizes research community • Provides safe training opportunities to new researchers

  19. Intellectual Benefits • Promotes understanding of past, change • Enables examination of problems comparatively • Improves knowledge through replication and enlargement • Elevates and enlarges theories about “what works”

  20. Caveats • Practice research ethically • Give credit where due • Respect confidentiality of respondents • Respect research in progress • Identify “strings attached” • Don’t “step on toes” (re: others’ plans) • Ask questions about data quality • Don’t lose sight of research needs • Avoid excessive items just to generate data • Avoid excessive “piggybacking”

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