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Relative Risk Calculator

Calculate relative risk (risk ratio), absolute risk reduction (ARR), relative risk reduction (RRR), and number needed to treat (NNT) from exposed and unexposed group data. Compare event rates between groups to quantify treatment effects and exposure risks — essential for clinical trials and epidemiological research.

Relative Risk Calculator — 실시간 비율 미리보기
Relative Risk
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        What is Relative Risk?

        Relative risk (RR), also called the risk ratio, compares the probability of an event occurring in an exposed group to the probability in an unexposed group. An RR of 2.0 means the exposed group is twice as likely to experience the event. An RR of 0.5 means the exposed group has half the risk — indicating a protective effect. RR = 1.0 means no difference between groups.

        Relative risk is the standard effect measure for prospective cohort studies and randomized controlled trials, where participants are followed forward in time from exposure to outcome. Unlike the odds ratio (used in case-control studies), RR directly compares probabilities and is more intuitive: RR 2.0 genuinely means 'twice the risk.' This calculator also computes the absolute risk reduction and number needed to treat for clinical decision-making.

        적용 수학 공식 및 방정식

        이 Relative Risk Calculator는 5가지 핵심 수학 공식을 사용합니다:

        1 Relative Risk ▼
        RR = (a / (a + b)) / (c / (c + d))

        Risk in exposed = a/(a+b). Risk in unexposed = c/(c+d). RR is their ratio.

        2 Absolute Risk Reduction ▼
        ARR = Risk_unexposed - Risk_exposed

        If control risk = 20% and treatment risk = 12%: ARR = 20% - 12% = 8 percentage points.

        3 Number Needed to Treat ▼
        NNT = 1 / ARR

        ARR of 8%: NNT = 1/0.08 = 12.5. You need to treat 13 patients to prevent 1 event.

        Explore all calculation options on the 비율 계산기 home page.

        비율 계산기 사용법

        이 비율 계산기는 아래의 3단계로 쉽게 사용할 수 있습니다:

        1

        수치 입력하기

        입력 칸에 알고 있는 비율 값을 입력합니다. 구하려는 미지수 자리의 칸 하나는 비워둡니다.

        2

        모드 선택하기

        비율 모드(풀기, 간소화, 스케일링)를 선택합니다. 각 모드는 입력한 수치에 맞춰 다른 공식들을 적용합니다.

        3

        결과 확인하기

        계산하기 버튼을 누릅니다. 결과 화면에 정답과 함께 시각적인 비율 바, 원형 차트, 상세한 단계별 풀이 과정이 출력됩니다.

        실제 예제 문제 및 단계별 풀이

        비율 계산기를 활용하여 아래 3가지 예제 문제를 단계별로 해결하는 과정입니다:

        입력 1 Drug trial: treated group vs placebo
        1 Treated group: 10 events out of 500 patients (Risk_treated = 10 / 500 = 0.02 or 2%).
        2 Placebo group: 50 events out of 500 patients (Risk_placebo = 50 / 500 = 0.10 or 10%).
        3 Relative Risk: RR = 0.02 / 0.10 = 0.20.
        4 Relative Risk Reduction: (1 - 0.20) × 100% = 80%.
        ✓ Relative Risk is 0.20 (80% Risk Reduction)
        입력 2 Smoking and heart disease (cohort study)
        1 Smokers: 120 heart attacks per 1,000 person-years (Risk_1 = 0.12).
        2 Non-smokers: 30 heart attacks per 1,000 person-years (Risk_0 = 0.03).
        3 Relative Risk: RR = 0.12 / 0.03 = 4.00.
        ✓ Relative Risk is 4.00 (4× Higher Incidence)
        입력 3 Calculate NNT for a vaccine
        1 Absolute Risk Reduction (ARR): 0.10 - 0.02 = 0.08 (8%).
        2 Number Needed to Treat (NNT): 1 / ARR = 1 / 0.08 = 12.5.
        ✓ NNT is 13 patients to prevent one adverse event

        자주 묻는 질문 (FAQ)

        What does a relative risk of 1.0 mean? ▼

        RR = 1.0 means the event rate is identical in both groups — no association between the exposure and the outcome. The exposure neither increases nor decreases risk. Values above 1.0 indicate increased risk; values below 1.0 indicate decreased risk (protection).

        How is relative risk different from odds ratio? ▼

        RR compares probabilities (events ÷ total), while OR compares odds (events ÷ non-events). For rare outcomes (< 10% incidence), they produce similar values. For common outcomes, OR systematically overstates the association compared to RR. RR is more intuitive ('twice the risk') and preferred when calculable.

        What is a clinically significant relative risk? ▼

        This depends entirely on context. For cancer screening, RR = 0.80 (20% risk reduction) may be highly significant. For a vaccine against a lethal disease, RR = 0.05 (95% efficacy) is transformative. Always consider absolute risk reduction and NNT alongside RR for clinical significance assessment.

        Can relative risk be used in case-control studies? ▼

        No. Case-control studies select participants based on outcome (cases vs. controls), not exposure. This design does not allow calculation of incidence rates, so RR cannot be computed. Use the odds ratio instead, which is the appropriate effect measure for case-control designs.

        What is the number needed to treat (NNT)? ▼

        NNT = 1 ÷ Absolute Risk Reduction. It represents how many patients must receive the treatment to prevent one additional adverse event. Lower NNT = more effective treatment. NNT of 10 means treating 10 patients prevents 1 event; NNT of 100 means treating 100 patients prevents 1 event.

        How do I calculate vaccine efficacy from relative risk? ▼

        Vaccine Efficacy = (1 - RR) × 100%. If vaccinated group has 5 infections per 1,000 and unvaccinated has 50 per 1,000: RR = 5/50 = 0.10. Efficacy = (1 - 0.10) × 100% = 90%. The vaccine reduces infection risk by 90%.

        What is the difference between relative risk reduction and absolute risk reduction? ▼

        RRR = (1 - RR) × 100%. ARR = Risk(control) - Risk(treatment). If control risk is 20% and treatment risk is 12%: RR = 0.60, RRR = 40%, ARR = 8 percentage points, NNT = 13. RRR sounds more impressive but ARR and NNT are more clinically informative.

        How do I interpret a relative risk less than 1? ▼

        RR < 1 indicates the exposure or treatment is protective — it reduces the risk of the outcome. RR 0.70 means a 30% lower risk in the exposed/treated group. RR 0.50 means half the risk. The closer to 0, the stronger the protective effect.

        When should I use relative risk vs. hazard ratio? ▼

        Use RR for fixed-time comparisons (what percentage had the event by time X). Use HR for time-to-event analysis where follow-up varies and you need to account for censoring. HR from Cox regression is preferred for survival analysis; RR from simple proportion comparison is used for fixed-duration studies.

        How does sample size affect relative risk precision? ▼

        Larger samples produce narrower confidence intervals around the RR estimate. A small study might produce RR = 0.60 with CI 0.20-1.80 (non-significant), while a larger study with the same effect produces RR = 0.60 with CI 0.45-0.80 (significant). Sample size does not change the point estimate but affects the precision.

        비율 이론 학습하기

        비율이란 정확히 무엇인가요?

        비율(Ratio)은 두 가지 이상의 양의 크기를 서로 견주어 비교해 나타낸 수치입니다. 기호로는 A : B 와 같이 나타내며, '앞엣것 A의 단위량당 뒤엣것 B의 분량이 매칭된다'는 상호 관계입니다. 3 : 4 비율이라면 A가 3개 배분될 때 B는 4개 매칭된다는 정비례 관계를 갖습니다. 요리 레시피 배량, 기계 설계, 금융 재무 분석 등에 두루 사용됩니다.

        비례식은 어떻게 푸나요?

        비례식은 두 비율의 가치가 같다는 것을 뜻하는 수학 등식입니다 (A : B = C : D). 외항의 곱(A × D)과 내항의 곱(B × C)은 항상 같습니다. 미지수 D를 구하려면 내항을 곱한 뒤 남은 외항 A로 나눕니다: D = (B × C) / A. 비율 계산기의 비례식 해결 모드에 알고 있는 세 숫자를 넣으면 미지수를 즉각 도출할 수 있습니다.

        비율은 어떻게 간단하게 정리하나요?

        두 숫자의 최대공약수(GCD)를 구한 다음 두 수를 모두 그 최대공약수로 나누어 약분하면 됩니다. 예컨대 24 : 36 의 경우 24와 36의 최대공약수가 12이므로 양쪽을 12로 나누면 가장 간단한 자연수의 비인 2 : 3이 됩니다. 비율 계산기가 GCD 연산과 약분을 자동으로 처리해 줍니다.

        비율 크기 스케일링은 언제 사용하나요?

        비율 관계를 흩뜨리지 않고 전체 양을 늘리거나 줄일 때 사용합니다. 예컨대 2 : 5 비율의 자재가 있을 때 양쪽 모두에 3을 곱하면 6 : 15 가 되어 동일한 비중을 가지면서 3배 많은 배합물을 준비할 수 있습니다. 빵 굽기 반죽 용량 증감, 조립 도면 축소 스케일링 등에서 필수적입니다.

        비율과 분수의 차이점은 무엇인가요?

        비율(A : B)은 대등한 성분끼리 양의 크기를 비교하는 것(부분 대 부분)에 가깝고, 분수(A/B)는 전체 수량의 파이 속에서 특정 부위가 차지하는 지분율(부분 대 전체)을 표현하는 경우가 많습니다. 다만 비율 3 : 4 역시 분수 3/4 (소수 0.75)의 가치로 나타낼 수 있습니다. 쓰임새와 의미 맥락에서 미세한 뉘앙스 차이가 존재합니다.