A 52-year-old man with hypertension (BP 168/98 mmHg, HR 88, RR 16, Temp 37.2°C) undergoes evaluation for cardiovascular risk. A regression model predicts systolic blood pressure using body mass index (32 kg/m²), waist circumference (104 cm), and body fat percentage (28%). Each variable individually correlates with blood pressure, but when entered together their coefficients become unstable with markedly elevated standard errors. Recent lipid panel is unremarkable. Which statistical problem best explains this pattern?
- A)MulticollinearityGABARITO
- B)Hawthorne effect
- C)Effect modification
- D)Differential misclassification
- E)Right censoring
Explicação
Multicollinearity occurs when predictor variables are highly correlated with one another, making it difficult for the model to distinguish their independent effects. This often leads to unstable coefficients and inflated standard errors despite good overall pr... Ver explicação completa e trilha adaptativa →