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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 — リアルタイム比率プレビュー
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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.

        使用される計算公式・方程式

        この計算ツールは5つの主要な公式を使用しています:

        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 比率計算ツール home page.

        比率計算ツールの使い方

        この比率計算ツールは、以下の3ステップで簡単にご利用いただけます:

        1

        数値を入力

        入力欄に既知の比率の値を入力します。求めたい未知数の入力欄は空欄のままにしておきます。

        2

        モードを選択

        比率モード(解く、簡素化、スケーリング)を選択します。各モードで異なる計算式が適用されます。

        3

        結果を確認

        計算するボタンを押します。結果画面に答えと、視覚的な比率バー、円グラフ、詳細なステップバイステップの解決プロセスが表示されます。

        実例問題と段階的な解説

        本比率計算ツールを使って、以下の3つの例題をステップバイステップで解決するプロセスです:

        入力 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)
        入力 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)
        入力 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

        よくある質問 (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.

        比率の理論を学ぶ

        比率とは具体的に何ですか?

        比率とは、2つ以上の数量の大きさを互いに比較して相対的な割合を表した数値です。記号では A : B のように表し、「Aの量に対してBの量が対応する」という相互関係を意味します。例えば、3 : 4 の比率は、Aが3つ分配されるときBは4つマッチするという正比例関係を持ちます。料理、工学設計、財務分析など日常のあらゆる場面で使われます。

        比例式はどのように解きますか?

        比例式は、2つの比率の値が等しいことを表す等式です(A : B = C : D)。外項の積(A × D)と内項 of 積(B × C)は常に等しくなります。未知数 D を求めるには、内項の積を求め、それをもう一方の外項 A で割ります: D = (B × C) / A。当ツールの比例式解決モードに既知の3つの数値を入力すれば、未知数を即座に算出できます。

        比率はどのように簡単に整理しますか?

        2つの数値の最大公約数(GCD)を求めた後、両方の数値をその最大公約数で割って約分します。例えば 24 : 36 の場合、24と36の最大公約数が 12 なので、両方を 12 で割ると最も簡単な自然数の比である 2 : 3 になります。比率計算ツールがGCDの算出と約分を自動的に処理します。

        比率のスケーリングはいつ使用しますか?

        比率の関係を崩さずに全体の分量を増やしたり減らしたりするときに使用します。例えば、2 : 5 の割合の材料があるとき、両方に 3 を掛ければ 6 : 15 になり、同じ比重を保ったまま3倍の量の配合物を準備することができます。パン生地の容量変更や、図面の縮尺変更に欠かせません。

        比率と分数の違いは何ですか?

        比率(A : B)は同等の要素同士の大きさの比較(部分対部分)に適しており、分数(A/B)は全体の中である要素が占める割合(部分対全体)を表現することが多いです。ただし、比率 3 : 4 も分数 3/4(小数で0.75)として表現できます。使われる文脈や意味合いにおいてニュアンスの違いがあります。