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Table 12 Ovarian Cancer – Predicted Regression Model Summaries

From: Geotemporospatial and causal inferential epidemiological overview and survey of USA cannabis, cannabidiol and cannabinoid genotoxicity expressed in cancer incidence 2003–2017: part 3 – spatiotemporal, multivariable and causal inferential pathfinding and exploratory analyses of prostate and ovarian cancers

Linear Models

Parameter

Model

Term

Estimate (C.I.)

P_Value

Adj.R.Squared

S.D.

t-Value

P -Value

Linear Model

 Percentile

0.016 (0.0157, 0.0166)

2.52E-87

0.9811

0.0656

5185.35

2.52E-87

Cubic Polynomial Model

 First Order Percentile

4.728 (4.657, 4.799)

2.58E-111

0.9944

0.0358

5898.511

1.31E-109

 Second Order Percentile

−0.177 (−0.248, − 0.106)

3.15E-06

    

 Third Order Percentile

0.521 (0.449, 0.591)

3.91E-26

    

Quintic Polynomial Model

 First Order Percentile

4.728 (4.698, 4.757)

1.19E-145

0.9991

0.0149

20,617.98

1.59E-142

 Second Order Percentile

−0.177 (−0.206, − 0.147)

1.45E-20

    

 Third Order Percentile

0.520 (0.491, 0.550)

3.85E-56

    

 Fourth Order Percentile

0.244 (0.215, 0.274)

1.43E-29

    

 Fifth Order Percentile

0.208 (0.178, 0.237)

7.22E-25

    

GAM Models

Parameter

Model

Term

Estimated Degrees of Freedom

Residual Degrees of Freedom

statistic

P_Value

Log.Likelihood

Aliake Information Criterin

Bayesian Information Criterion

Smoothened Percentile

8.8097

8.9893

8777.844

1.46E-19

273.484

−525.3486

−497.0799