Likelihood Ratio Calculator
The Likelihood Ratio Calculator computes positive likelihood ratio (LR+) and negative likelihood ratio (LR-) from a diagnostic test's sensitivity and specificity. Evaluate how much a test result shifts the probability of disease for evidence-based clinical decisions.
🕐 Recent Calculations
What is a Likelihood Ratio?
A likelihood ratio quantifies how much a test result changes the probability of having a condition. The positive likelihood ratio (LR+) measures how much a positive test increases disease probability. The negative likelihood ratio (LR-) measures how much a negative test decreases it. LR+ above 10 or LR- below 0.1 are considered strong evidence.
Likelihood ratios combine sensitivity and specificity into a single metric that is independent of disease prevalence. Clinicians use LRs with pre-test probability (Bayesian reasoning) to calculate post-test probability, making them more useful than sensitivity/specificity alone for clinical decision-making.
Kullanılan Formüller & Denklemler
Bu Likelihood Ratio Calculator aracı 5 temel denklem kullanır:
1 Positive Likelihood Ratio ▼
Sensitivity 95%, Specificity 90%: LR+ = 0.95 / (1 - 0.90) = 0.95 / 0.10 = 9.5.
2 Negative Likelihood Ratio ▼
Sensitivity 95%, Specificity 90%: LR- = (1-0.95) / 0.90 = 0.05 / 0.90 = 0.056.
3 Post-Test Odds (Fagan Nomogram) ▼
Pre-test probability 20% → odds = 0.25. LR+ = 9.5 → Post-test odds = 0.25 × 9.5 = 2.375 → probability = 70.4%.
Bu Hesaplayıcı Nasıl Kullanılır?
Bu Oran Hesaplayıcıyı kullanmak için 3 adımı takip edin:
Değerleri Girin
Bilinen oran değerlerini giriş alanlarına yazın. Bir alanı boş bırakın — Oran Hesaplayıcının çözdüğü bilinmeyen değer budur.
Mod Seçin
Oran modunu seçin — Çöz, Basitleştir veya Ölçeklendir. Her mod, giriş değerlerinize farklı denklemler uygular.
Sonuçları Alın
Hesapla'ya tıklayın. Sonuç ekranı, cevabı görsel bir oran çubuğu, pasta grafiği ve adım adım çözüm dökümü ile görüntüler.
Örnek Problemler & Adım Adım Çözümler
İşte bu Oran Hesaplayıcıyı kullanan adım adım çözümlü 3 örnek problem:
Giriş 1 Test with 90% sensitivity, 85% specificity
Giriş 2 Calculate post-test probability
Giriş 3 Highly sensitive test: 99% sensitivity, 50% specificity
Sıkça Sorulan Sorular
What is a good likelihood ratio? ▼
LR+ > 10 is strong evidence for disease. LR+ 5-10 is moderate. LR+ 2-5 is weak. LR- < 0.1 strongly rules out disease. LR- 0.1-0.2 is moderate. LR values near 1.0 provide no useful information.
Why are likelihood ratios better than sensitivity/specificity? ▼
LRs combine both metrics into a single number and are independent of disease prevalence. They can be applied directly to individual patients using pre-test probability. Sensitivity and specificity are prevalence-independent but don't directly give post-test probability.
How do I use the Fagan nomogram? ▼
Draw a line from your pre-test probability (left axis) through the likelihood ratio (middle axis) to find the post-test probability (right axis). This visual tool quickly converts LRs into clinically useful probability changes.
Can likelihood ratios be used for multi-level test results? ▼
Yes. Interval likelihood ratios can be calculated for different result ranges (e.g., low, moderate, high values) rather than just positive/negative. Each interval has its own LR for more nuanced interpretation.
What is pre-test probability? ▼
Pre-test probability is your estimated chance of disease before conducting the test, based on prevalence, symptoms, and clinical judgment. It's the starting point for Bayesian reasoning with likelihood ratios.