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Overview of Quantitative Research Methods

Overview of Quantitative Research Methods. Training Overview. Describes when quantitative analyses are appropriate Provides an overview of four techniques Describing the central tendency and variation in a group Analyzing trends in program expenditures Regression analysis Survival analysis.

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Overview of Quantitative Research Methods

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  1. Overview of Quantitative Research Methods

  2. Training Overview • Describes when quantitative analyses are appropriate • Provides an overview of four techniques • Describing the central tendency and variation in a group • Analyzing trends in program expenditures • Regression analysis • Survival analysis

  3. Elements of a Finding • Criteria • Condition • Significance • Cause • Recommendation

  4. Questions Addressed by Quantitative Analysis • How typical? • What fraction? • How many or how much? • What has changed? • How does one group compare with other groups?

  5. The Power of Quantitative Analysis • Where anecdotes can provide rich descriptions of a few, quantitative analysis can be used to describe large aggregates • Quantitative analysis enjoys the legitimacy of the “objectivity” promised by mathematical analysis

  6. Techniques • Describing groups - central tendency and variation • Analyzing trends in program expenditures • Regression analysis • Survival analysis

  7. Central Tendency and Variation Mean (average) Median Mode Range

  8. Avg. = $40,300 Teacher Salaries: District A

  9. Avg. = $40,300 Teacher Salaries: District B

  10. Avg. = $40,300 Teacher Salaries: District C

  11. Avg. = $40,300 Teacher Salaries: District D

  12. Analyzing Trends in Expenditures Annual percent change Average annual percent change Disaggregating expenditures

  13. Measures of Change Annual percent change ($T2 - $T1) / $T1 or ($T2 / $T1) - 1 Average annual percent change ($T5 / $T1) 1 / (# years*) – 1 * # of years = 4 in this case

  14. Trends in Medicaid Expenditures

  15. Disaggregating Expenditures Into Factors Driving Expenditures

  16. Regression Analysis Y = a + B(X1) + B(X2) + B(X3) + . . . Regression analysis estimates Y given values of X1, X2, X3, etc. The Bs indicate the independent effect the Xs have on Y.

  17. Estimating Hospice Expenditures

  18. Estimating Hospice Expenditures

  19. Estimating Hospice Expenditures

  20. Examining Cost Effectiveness

  21. Examining Cost Effectiveness

  22. Survival Analysis Kaplan-Meier Cox regression

  23. Survival Analysis – How Long Until?

  24. Review Under what conditions is the mean (average) not the best measure of central tendency? What are the best measures of central tendency under these conditions?

  25. Review Why is using the geometric mean for the average annual percent change more appropriate than average of the annual percent changes in column B?

  26. Review What are some instances where it would be important to adjust for the characteristics of members of a group when comparing multiple groups on an outcome (e.g., cost effectiveness)? Would regression analysis be appropriate?

  27. Review Survival analysis techniques are a better alternative to estimating how long it takes an event to occur (e.g., release from a treatment facility). What is the disadvantage of the more commonly used average length of stay for persons released in a year?

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