Table 5.
Prostate Cancer – Predictive Regression Model Summaries
Linear Models | ||||||||
Parameter | Model | |||||||
Term | Estimate (C.I.) | P_Value | Adj.R.Squared | Standard Deviation | t-Value | P -Value | ||
Linear Model | ||||||||
Percentile | 0.95 (0.92, 0.97) | 2.52E-87 | 0.9811 | 3.8586 | 5185.354 | 2.52E-87 | ||
Cubic Polynomial Model | ||||||||
First Order Percentile | 277.86 (273.73, 281.98) | 2.58E-111 | 0.9943 | 2.1028 | 5898.511 | 1.31E-109 | ||
Second Order Percentile | −10.41 (− 14.53, − 6.28) | 3.15E-06 | ||||||
Third Order Percentile | 30.61 (26.49, 34.73) | 3.91E-26 | ||||||
GAM Model | ||||||||
Parameter | Model | |||||||
Term | Estimated Degress of Freedom | Residual Degrees of Freedom | Statistic | P -Value | Log.Likelihood | Akaike Information Crierion | Bayesian Information Criterion | |
Smoothened Percentile | 8.8184 | 8.9902 | 8777.838 | < 2.2E-320 | − 137.9338 | 297.5044 | 325.7959 |