Logistic Regression (Binary)

Analyze binary outcomes using logistic regression. Compute Odds Ratios and assess model fit.

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n = 0Outcome
n = 0Risk Factor
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10 Rows Γ— 2 Columns

Logistic Regression (Binary)

Enter binary (0/1) outcome data to run logistic regression.

Formula

Logistic Regression

Probability of Event:

P(Y=1)=11+eβˆ’(Ξ²0+Ξ²1X1+...)P(Y=1) = \frac{1}{1 + e^{-(\beta_0 + \beta_1 X_1 + ...)}}

Logit (Log-Odds):

ln⁑(P1βˆ’P)=Ξ²0+Ξ²1X1+...\ln\left(\frac{P}{1-P}\right) = \beta_0 + \beta_1 X_1 + ...

Odds Ratio (OR):

ORj=eΞ²jOR_j = e^{\beta_j}

Parameters are estimated using Maximum Likelihood Estimation (MLE) via Newton-Raphson.