Exploring Predictive Models and Statistical Significance
Welcome Back! In this blog we will aim to investigate the relationship between pemax (maximum peak expiratory pressure) and potential predictors as well as develop a predictive model for birth weight based on fetal measurements in the secher dataset. 1. INPUT: OUTPUT: I analyzed the impact of age , weight , bmp , and fev1 on pemax in the cystfibr dataset using a multivariate linear regression model and ANOVA. Regression Analysis : The regression model indicated that fev1 had a significant positive effect on pemax (estimate = 1.5, p < 0.01), suggesting that higher fev1 values are associated with an increase in pemax . However, age (estimate = -0.2, p = 0.3) and weight (estimate = 0.3, p = 0.4) did not significantly predict pemax . ANOVA : The ANOVA results reinforced the regression findings, showing a significant F-value for fev1 (F = 8.45, p < 0.01), while age and weight did not have statistically significant contributions (p > 0.05). 2. INPUT OUTPUT R...
