How Do We Combine Many Studies Into One Answer?
Experimental Design domain · Lesson 17 of 20 · Biomedical Innovations (BI)
Today's goal: Explain how a systematic review pools studies using PRISMA, read a PRISMA flow diagram, and state when studies are too different to combine (heterogeneity).
This is a model of the work you should turn in. Use it to check your own: match the structure and the level of detail, do not copy it. Your wording should be your own.
1. Pool the 3 studies that used the same validated speech test; keep the 1 home-made-test study separate, because pooling a different outcome definition would average apples and oranges and inflate heterogeneity.
2. The '?' becomes 3: only the 3 matched-test studies go into the meta-analysis.
3. Advice to the PI: The review can honestly conclude only about the 3 comparable studies; the odd-test study should be described narratively, not folded into the pooled number.
This model shows the level of evidence and organization needed to complete: A Data Scientist's call on which studies to pool, with the heterogeneity reason.
- Name the variables and include units.
- Enter observations without changing the raw values.
- Check labels, calculations, and patterns before interpreting the data.
Keep the structure. Replace the question, facts, measurements, and evidence. Then recheck units, vocabulary, and whether the conclusion goes beyond the evidence.
The finished product above did not appear all at once. Here is the path from the question to the turned-in work, so you can follow the same steps.
- 1Start from today's question: Which records are found before the sieve?
- 2Work the Model and the Explore questions to reason it out before writing anything.
- 3Pull the specific evidence the product needs from the reading and any database you used.
- 4Write it up in the required format: Use the flow diagram. Of the 4 included studies, suppose 3 measured speech with the same validated test and 1 used a completely different home-made test. As Data Scientist: (1) which studies could you reasonably pool, and which one would you keep separate, and why? (2) fill the '?' in the diagram: how many studies go into the meta-analysis under your decision? (3) write one sentence telling the PI what the review can honestly conclude.
- 5Check it against the rubric, then submit.
| Criterion | Proficient | Developing | Beginning |
|---|---|---|---|
| Complete | Every required part of the artifact is present and filled in. | Most parts are present, but one is missing or left blank. | Several parts are missing. |
| Accurate | The science and data are correct and match the evidence. | Mostly correct, with a small factual slip. | Key science or data is wrong. |
| Scientific reasoning (CER) | States a claim, backs it with specific evidence, and explains the reasoning. | Has a claim and evidence, but the reasoning is thin or missing. | Gives an answer with no evidence or reasoning. |
| Professional communication | Clear, organized, and labeled the way a clinician or scientist would write it. | Readable but disorganized or missing labels. | Hard to follow. |
| Submitted | Turned in through the route named under Submit here and confirmed. | Turned in, but in the wrong place or unconfirmed. | Not turned in. |
- CompleteProficient: Nothing is left blank: the model fills every part of "Use the flow diagram. Of the 4 included studies, suppose 3 measured speech with the same validated test and 1 used a completely different home-made test. As Data Scientist: (1) which studies could you reasonably pool, and which one would you keep separate, and why? (2) fill the '?' in the diagram: how many studies go into the meta-analysis under your decision? (3) write one sentence telling the PI what the review can honestly conclude.".
- AccurateProficient: Every number and claim matches the case evidence.
- Scientific reasoning (CER)Proficient: It names a claim, cites the specific evidence, and explains the reasoning, not just the answer.
- Professional communicationProficient: It is organized and labeled like a real chart note.
- SubmittedProficient: It would be attached to your class form or handed in, and confirmed.
One exam-style question that uses exactly what you practiced today. Try it before you reveal the answer, then read why each choice is right or wrong.
Tap an answer to see the full explanation. Nothing is recorded or graded.
It builds this reusable test skill: Deciding when heterogeneity means studies should not be pooled.
- Name the concept or data pattern being tested.
- Cross out choices that violate that rule or the evidence.
- Justify the best remaining choice before checking the answer.