cassionData Analysis

Back to the lessonLesson 8 of 8What the evaluation claims

The evaluation that declines the question

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  1. Slide 1 / 16

    What this lesson covers

    • Assemble what the course produced
    • The summary that is honest
    • Four sentences an evaluation must be able to write
    • What "no effect detected" is worth
    • Writing for the reader who will quote one sentence
    • What the course has been about
    • Report it whole
    • What comes next
    Speaker notes
    The commission asked whether school feeding raises learning. The honest answer is that this design could not have detected an effect of the size the programme cares about, that what it did detect is nothing, and that both statements have to appear in the summary rather than the annex.
  2. Slide 2 / 16

    Assemble what the course produced

    QuestionAnswerWhere it came from
    Did scores rise?+6.97 pts, 95% CI +6.1 to +7.9Before-after, lesson 1
    Is that the programme?No — comparison schools rose 7.62Lesson 1
    Are the groups comparable?No — six of six characteristics imbalancedBalance table, lesson 2
    What is the effect?−0.96 pts, 95% CI −3.5 to +1.6Difference-in-differences, lesson 3
    Does matching change it?−0.71 pts, on 9 of 15 treated schoolsLesson 4
    Could a better design run?Not on this data — no outcome past the cut-offLesson 5
    What could it have detected?Nothing below 4.9 pointsPower, lesson 6
    Speaker notes
    Seven lessons, one programme, one file. Here is everything the analysis established.
  3. Slide 3 / 16

    Assemble what the course produced

    • Two of those seven rows are the report and the other five are the annex — The finding is the fourth row and the…
    Speaker notes
    Two of those seven rows are the report and the other five are the annex. The finding is the fourth row and the seventh, and the seventh is the one that has to lead.
  4. Slide 4 / 16

    The summary that is honest — Example (cont.)

    School feeding and learning outcomes: evaluation summary
    
      FINDING
    
      This evaluation cannot answer whether the school feeding programme
      improves literacy, and the reason is in its design rather than its
      results.
    
      The programme is delivered in 15 schools and compared against 9. With
      fifty children per school and the observed clustering, the smallest
      effect this comparison could have detected is 4.9 percentage points. The
      programme team's threshold for expansion is 3 points. The evaluation was
      therefore incapable of answering the question it was commissioned to
      answer, and this was knowable before it began.
    
      What it does establish: literacy rose 7.0 points over the school year in
  5. Slide 5 / 16

    The summary that is honest — Example (cont.)

      both programme and comparison schools, with no difference between them
      (-0.96 points, 95% CI -3.5 to +1.6). Effects larger than 3.5 points in
      either direction are ruled out. Effects between 0 and 3 points -- the
      range the programme cares about -- are not.
    
      RECOMMENDATION
    
      Do not discontinue the programme on the basis of this evaluation. Do not
      expand it on the basis of the 7-point gain, which is the school year and
      is present in schools without the programme.
    
      To answer the question, an evaluation needs about 60 schools rather than
      24. If the programme is expanding to new schools, randomising the order of
      the roll-out costs nothing and produces a comparison group that does not
      have to be argued for.
  6. Slide 6 / 16

    The summary that is honest

    • The first paragraph refuses the question and the last paragraph says what would answer it — Between them there is a…
    Speaker notes
    The first paragraph refuses the question and the last paragraph says what would answer it. Between them there is a finding, an interval and a boundary, and no number is presented as an effect that is not one.
  7. Slide 7 / 16

    Four sentences an evaluation must be able to write

    • "The counterfactual is X." — Here: schools without the programme, assumed to have been on the same trajectory
    • "The estimate is Y, with interval Z, in units the programme uses." — Here: −0.96 percentage points of literacy, −3.5 to…
    • "The smallest effect this design could detect is W." — Here: 4.9 points
    • "This analysis cannot rule out V." — Here: any effect between zero and about three points, which is the whole range the…
    Speaker notes
    Each one is a check on the report, and a report that cannot produce all four has a gap. "The counterfactual is X." Here: schools without the programme, assumed to have been on the same trajectory. "The estimate is Y, with interval Z, in units the programme uses." Here: −0.96 percentage points of literacy, −3.5 to +1.6, where 3 points is the threshold of interest. "The smallest effect this design could detect is W." Here: 4.9 points. This is the sentence most evaluations lack, and its absence is what lets a null be read as a refutation. "This analysis cannot rule out V." Here: any effect between zero and about three points, which is the whole range the programme is arguing about.
  8. Slide 8 / 16

    What "no effect detected" is worth

    ReadingSupported?
    "The programme does not work"No — the design could not detect the relevant effect
    "The programme has no large effect on literacy"Yes — above 3.5 points is ruled out
    "The 7-point gain is not attributable to the programme"Yes — comparison schools gained more
    "Funding should be redirected"No — that requires an effect estimate this study does not have
    "The next evaluation needs 60 schools"Yes — computed, and actionable
    Speaker notes
    It is worth something, and being precise about how much is the difference between a useful null and a damaging one.
  9. Slide 9 / 16

    What "no effect detected" is worth

    • The two "yes" rows in the middle are real findings and they are unwelcome ones — they take away a headline number a…
    Speaker notes
    The two "yes" rows in the middle are real findings and they are unwelcome ones: they take away a headline number a programme had been using. Delivering that is the job, and doing it alongside the recommendation in the last row is what makes it receivable.
  10. Slide 10 / 16

    Writing for the reader who will quote one sentence

    • Not — "No statistically significant effect of school feeding on literacy was found." True, and it will be read as "the…
    • Not — "Literacy rose 7 percentage points in programme schools." True, and it will be read as the effect
    • This — "Literacy rose 7 points in both programme and comparison schools; this evaluation was not large enough to detect…
    • Put that sentence in the summary, the conclusion and the covering email — The quotable line is chosen by you or it is…
    Speaker notes
    Someone will extract one line from this report and put it in a slide. Decide now which line that is. Not: "No statistically significant effect of school feeding on literacy was found." True, and it will be read as "the programme does not work". Not: "Literacy rose 7 percentage points in programme schools." True, and it will be read as the effect. This: "Literacy rose 7 points in both programme and comparison schools; this evaluation was not large enough to detect the 3-point difference the programme cares about." Put that sentence in the summary, the conclusion and the covering email. The quotable line is chosen by you or it is chosen for you.
  11. Slide 11 / 16

    What the course has been about

    • Which means the most consequential decisions were made before any data existed — who got the programme and in what…
    • So the useful thing this course asks for is not a technique — It is being in the room in January, with one page, asking…
    Speaker notes
    Eight lessons and one idea: an impact claim is a comparison with an absent half, and the design is the argument about what fills it. Every method here — randomisation, difference-in-differences, matching, discontinuity — is a different argument for the same missing quantity, and each is stronger or weaker depending on facts about how the programme was rolled out rather than on anything in the analysis. Which means the most consequential decisions were made before any data existed: who got the programme and in what order, what was measured and on whom, and how many units were assigned. An analyst who arrives afterwards is choosing among the arguments the roll-out left available. So the useful thing this course asks for is not a technique. It is being in the room in January, with one page, asking how the schools will be chosen and whether the order can be randomised — which is a question that costs nothing to ask and is unanswerable a year later.
  12. Slide 12 / 16

    Report it whole — Example (cont.)

    Evaluation of the school feeding programme: methods and limitations
    
      Design            Difference-in-differences, 15 programme and 9
                        comparison schools, baseline and endline literacy on
                        585 students with both rounds.
    
      Counterfactual    Comparison schools, assumed to have been on the same
                        trajectory. Two rounds exist, so parallel trends is
                        argued (numeracy shows the same null; no single school
                        drives the result) and not tested.
    
      Estimate          -0.96 percentage points, 95% CI -3.5 to +1.6,
                        clustered on 24 schools.
    
      Power             Minimum detectable effect 4.9 points at 80% power,
                        against a 3-point threshold of interest. Underpowered
  13. Slide 13 / 16

    Report it whole — Example (cont.)

                        for the relevant effect size.
    
      Balance           All six baseline characteristics imbalanced beyond 0.25
                        standardised. Adjusted for baseline and district;
                        unmeasured selection is not addressed.
    
      Attrition         585 of 741 baseline students have an endline. Those who
                        left scored 39.3% at baseline against 56.8% for those
                        who stayed.
    
      Not claimed       Any effect on attendance, enrolment or nutrition. Any
                        causal effect beyond the difference-in-differences
                        assumption. Any conclusion about effects below 3 points.
    
      Plan              Written 2024-01-15, one deviation listed in Annex A,
                        three exploratory analyses in Annex B.
  14. Slide 14 / 16

    Report it whole

    • Eight rows, and a reviewer can reconstruct every decision from them — That is the deliverable this course has been…
    Speaker notes
    Eight rows, and a reviewer can reconstruct every decision from them. That is the deliverable this course has been building toward: not a number, but a number surrounded by everything a reader needs in order to know what it is.
  15. Slide 15 / 16

    What comes next

    • Module 5 is complete: uncertainty, then models, then designs.
    Speaker notes
    Module 5 is complete: uncertainty, then models, then designs. Module 6 is about delivery — turning what you have established into something a programme can see, use and rebuild, which is the last thing standing between an analysis and a decision.
  16. Slide 16 / 16

    Where this goes next

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