Abbreviated Interrupted Time-Series - Institute for Policy Research

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Threats to Validity: Instrumentation • Instrumentation: the way the outcome was measured changed at the same time that the intervention was introduced. – In Chicago, when Orlando Wilson took over the Chicago <strong>Policy</strong> Department, he changed the reporting requirements, making reporting more accurate. The result appeared to be an increase in crime when he took office. – It is important to explore the quality of the outcome measure over time, to ask about any changes that have been made to how measurement is operationalized.
Threat to SCV • When a treatment is implemented slowly and diffusely, as in the alcohol warning label study, the researcher has to specify a time point at which the intervention “took effect” – Is it the date the law took effect? – Is it a later date (and if so, did the researcher capitalize on chance in selecting that date)? – Is it possible to create a “diffusion model” instead of a single date of implementation?
Page 1 and 2: Abbreviated Interrupted Time‐Seri
Page 3 and 4: The effect can be a change in inter
Page 5 and 6: The effect can be a change in slope
Page 7 and 8: The effect can be delayed in time.
Page 9 and 10: Interrupted Time Series Can Provide
Page 11 and 12: Meeting ITS Conditions in Education
Page 13 and 14: • O X O Theoretical Rationales fo
Page 15 and 16: O O O X O • Initial standing asse
Page 17: Threats to Validity: History • Wi
Page 21 and 22: External Validity • The essence o
Page 23 and 24: O X O O O • Now we add a comparis
Page 25 and 26: O O O X O O O O O • Now mean diff
Page 27 and 28: Results: Percent of Students Obtain
Page 29 and 30: Adding a nonequivalent dependent va
Page 31 and 32: Note that the outcome variable (ope
Page 33 and 34: Only the targeted dependent variabl
Page 35 and 36: Example: Evaluating No Child Left B
Page 37 and 38: Contrast Type 1 & 2 • Contrast 1:
Page 39 and 40: Hypothetical NCLB effects on public
Page 41 and 42: Analytic Model • NCLB Public vs.
Page 43 and 44: Main NAEP 4 th grade math scores by
Page 45 and 46: Difference in differences in Total
Page 49 and 50: Trend NAEP Time Series Graphs Publi
Page 51 and 52: Trend NAEP 8 th grade math scores b
Page 53 and 54: Public vs Private School Findings
Page 55 and 56: Contrast 2: Comparing States that v
Page 57 and 58: Evidence of Differing Standards Hig
Page 59 and 60: Main NAEP Time Series Graphs States
Page 61 and 62: ], ) ( ) ( ) ( [ ) _ _ ( ) _ _ ( )
Page 65 and 66: Difference in differences in 2009 T
Page 67 and 68: Overall Conclusions • Similar res
Page 69 and 70:
Basic Insight of D & J • NCLB pas
Page 71 and 72:
D & J Results: 4 th Grade Math
Page 73 and 74:
Dee and Jacob Results • Similar c
Page 75 and 76:
4 th Grade Reading
Page 77 and 78:
The Use of Multiple Comparison Grou
Page 79 and 80:
Adding Treatment Introduction and R
Page 81 and 82:
Medication decreased hyperactivity,
Page 83 and 84:
Example: Chorpita • A child with
Page 85 and 86:
Multiple Baselines on Different Uni
Page 88 and 89:
The effects of screening for phenyl
Page 90 and 91:
Multilevel Models: Current Work •
Page 92 and 93:
Potential drawbacks of using HLM to
Page 94 and 95:
Stuart Data Example (Stuart, 1967)
Page 96 and 97:
Level 2 data: Persons Level-2 data
Page 98 and 99:
HLM: Linear Model Estimates Final e
Page 100 and 101:
HLM Output from Quadratic Model: Fi
Page 102 and 103:
So Simple: What Could Go Wrong? •
Page 104 and 105:
Problematically • Different combi
Page 106 and 107:
Do you have any examples to share w
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