Clue 1: Orient yourself
Which group is selected because the event happened?
Use the labels and the picture's left-to-right, near-to-far, or before-and-after order. Name only what you can point to.
The question
Which group is selected because the event happened?
Why it matters: Clinical recommendations affect real children and families. Fair comparisons, bias control, ethical limits, and honest uncertainty keep a promising result from becoming a harmful claim. Today you practice the professional reasoning behind that work: Case-control studies efficiently study rare outcomes, but their odds ratios remain vulnerable to selection, recall, and confounding.
On your WebXam
Interpreting an odds ratio and its confidence interval in a case-control study
For life
To find the cause, change one thing and watch what changes.
Principle: Same look, different cause
Five principles we return to
Having it is not using it
Same instructions, different switches
Same look, different cause
Change one thing and watch
Boss or doorman?
Decides the result or only allows it
Held down, not gone
Remove the brake and it returns
Many roads, one ending
One result can begin many ways
Try the everyday version first
A detective starts with a rare event and looks backward for clues
A detective can begin with an unusual result and ask which earlier events could lead to it. The rarity guides the search but does not identify one cause.
Do not jump to the biology yet. Treat the picture as a small system. Track its parts, follow one change at a time, and keep more than one explanation open until the picture supplies a way to separate them.
Clue 2: Trace one change
Where does the search move in time?
Follow one object, stage, or path. Point to the first place where the situation changes instead of jumping to the ending.
Clue 3: Keep the cause open
Which clue could be remembered differently by the two groups?
List more than one explanation that still fits. Name the extra observation that would help you separate those possibilities.
Now inspect the illustration
Work from the visible evidence. A useful answer names the part of the picture that supports it and leaves unknown causes open.
- 1Which group is selected because the event happened?
- 2Where does the search move in time?
- 3Which clue could be remembered differently by the two groups?
Tier 1 check
Finish with the everyday model
Use the everyday picture to answer today's question in plain words: Which group is selected because the event happened?
You can complete today's required check without opening the technical details below.
Ready for the real names? Optional tier 2
Technical rules and limits
Rule 1: Select cases by outcome and comparable controls without it.
Rule 2: Measure prior exposure the same way.
Rule 3: Read an odds ratio with its interval and bias risks.
Where the analogy stops: Unlike a detective story, an association may have several explanations and may never identify one culprit.
Carry the previous idea forward
The strongest design is the one that fits the question and controls its main threats.
Today's technical takeaway
Case-control studies efficiently study rare outcomes, but their odds ratios remain vulnerable to selection, recall, and confounding.
Now map the same rules onto biology
Test a suspected exposure with a supplied 2 by 2 table
Rare event file
Cleft case group
Comparison file
Control group from the same population
Backward clue search
Prior exposure history
Educational illustration, not a clinical photograph or a patient-specific study plan. Use the supplied evidence cards and claim ceiling.
Mateo's case file: evidence supplied in this lesson
EXP04-E1
The table has 30 exposed and 70 unexposed cases, plus 15 exposed and 85 unexposed controls.
Why it matters: The odds ratio is about 2.4.
EXP04-E2
The reported 95 percent confidence interval is 0.9 to 3.4.
Why it matters: The interval includes 1.0, so the data remain compatible with no odds difference.
EXP04-E3
Parents of affected infants may recall an exposure differently while searching for an explanation.
Why it matters: Recall bias could inflate or reduce the observed association.
Make the clinical decision
You are the epidemiologist reviewing a suspected prenatal exposure.
The team must decide whether the supplied result proves that the exposure caused clefts.
AReport an uncertain association and plan better exposure measurement plus confounder control.
BDeclare the exposure proven causal because the odds ratio is above 1.
CDeclare no possible effect because the interval crosses 1.
Choose the interpretation and cite the odds ratio, interval, and one bias risk.
Evidence required
EXP04-E1 + EXP04-E2 Claim ceiling
You may report the observed association and uncertainty. You may not claim individual blame or causation.Go deeper Optional tier 3
Everything required for today is above. Open these only if you want the explainer, source trail, or download files.
The everyday model and Tier 1 check are the complete required path for this lesson.
Use these checks to keep your place. They are not turned in through the portal.
Check off as you finish
- Worked through the everyday picture and answered its three questions.
- Completed the Tier 1 check in plain words.
Turn in: Experimental Design lesson 4: Studying a Cause You Cannot Assign
Go to Schoology to turn this in.
Submit one PDF. Put your first and last name in the document header. Name the file: FirstName LastName - Assignment Title - YYYY-MM-DD.pdf.
Open Schoology PDF upload helpIf you cannot get in, see Mr. Mendoza. Do not skip the work.
Optional legacy technical materials Open only if you want the original notes, vocabulary, artifact, and CER work
Before this page, you should know
- The () ranks designs from weaker to stronger by how well each controls bias, a feature that pushes a result away from the truth.
- A has no comparison group; an (case-control, cohort) watches groups without assigning the exposure and can be misled by confounding.
If not, review
Today's new idea is only
A works backward from outcome to exposure, and the with its tells us whether the association is real.
Goal: Students will explain how a works backward from outcome to exposure, compute and interpret a simple with its , and name as its signature flaw.
Know by the end
- A starts with the outcome (cases versus controls) and looks backward at the suspected exposure; it is the workhorse for a rare outcome like a (about 1 in 700 births).
- The is the odds of exposure in cases divided by the odds in controls; above 1 suggests a , equal to 1 means no association, below 1 means less common in cases.
- If the includes 1.0, the association is not statistically significant because no effect is still plausible.
- The signature flaw is : mothers of affected babies may remember exposures differently, which can inflate the ; a teratogen is an agent that can disrupt development.
1
Working backward
Model start: A starts with the outcome and looks backward at exposure, the right design for a rare outcome like a .
- A starts with the outcome: you gather cases (babies with a ) and controls (similar babies without one), then look ____ (backward) in time at the suspected exposure.
- This is the workhorse for a rare outcome, because a happens in roughly 1 in 700 births and a forward study would need an enormous group to catch enough cases.
2
The odds ratio
- OR greater than 1 means the exposure is more common in cases (a possible ); OR equal to 1 means no association; OR less than 1 means it is ____ (less) common in cases.
- In the worked table, OR = (40/60) / (20/80) = 0.667 / 0.25 = about 2.7, meaning the odds of that exposure were about 2.7 times higher among cases.
3
Confidence interval and recall bias
- We report a around the OR; if the interval includes 1.0, the association is not statistically significant because no effect is still plausible.
- The signature flaw is : mothers of an affected baby may remember pregnancy exposures more intensely, which can inflate the OR; a also cannot give the true population rate of clefts.
Everything you need for today is on this page. These links are optional.
What to read
Read the short plain-language explanation written for this lesson. Plain-language explainer for this lesson
Why this source matters
This explanation gives you the background for today's idea without making you decode a research paper: A works backward from outcome to exposure, and the with its tells us whether the association is real.
Words to unlock first
Reading moves
- Skim the title and abstract first to get the gist.
- Circle the one sentence that states the main claim.
- Box the evidence the authors give for that claim.
- Mark one sentence that confuses you, and move on.
Stop point
Stop after the final 'Use it now' section. The research citations are available separately for advanced readers.
Your output
Write one claim-evidence sentence: state the main idea, then name the example or evidence that supports it.
Where this fits
Tested on (Ohio WebXam)
Genetics of Disease · 072130
PLTW lesson
MI · Experimental Design domain · Epidemiology, risk factors, and the case-control design
WebXam domain
Molecular and Genetic Technology
Evidence to produce
For a different exposure (cases: 30 exposed, 70 not; controls: 15 exposed, 85 not) build the 2-by-2 table, compute the odds ratio, decide using a reported 95 percent CI of 0.9 to 3.4 whether the association is significant, and write one recall-bias concern to raise before anyone calls the exposure a cause.
Lab / skill
Biomedical Innovations (BI) · Medical Interventions (MI)
Everything required for today's decision is already in the case file and plain-language explainer. The links below are original papers and database records for teachers and advanced readers, not assigned student reading.
- Claim: The worked exposure in Model 1 is associated with higher odds of a .
- Evidence: The is about ____, and an OR above 1 means the exposure was ____ common among cases.
- Reasoning: A can show this association without anyone assigning the exposure, but the link might still not be a true cause because of ____ ( or confounding).
How this is graded (rubric)
For: For a different exposure (cases: 30 exposed, 70 not; controls: 15 exposed, 85 not) build the 2-by-2 table, compute the odds ratio, decide using a reported 95 percent CI of 0.9 to 3.4 whether the association is significant, and write one recall-bias concern to raise before anyone calls the exposure a cause.
| 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. |
How the model answer scores against this rubric
- CompleteProficient: Nothing is left blank: the model fills every part of "For a different exposure (cases: 30 exposed, 70 not; controls: 15 exposed, 85 not) build the 2-by-2 table, compute the odds ratio, decide using a reported 95 percent CI of 0.9 to 3.4 whether the association is significant, and write one recall-bias concern to raise before anyone calls the exposure a cause.".
- 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.
What's next: The case-control design lets us chase causes from the outside world without assigning harm. But Mateo's sparse family history keeps nagging us. How would we measure how much of risk is inherited rather than environmental, when you cannot give a memory questionnaire about DNA?