Gaussian Copula Regression Modeling for Marker Classification Metrics with Competing Risk Outcomes

<div>Log-minus-log plot for AGE in the prostate cancer study data. Group 1 (AGE <svg height="8.98582pt" id="M364" style="vertical-align:-0.6370001pt" version="1.1" viewbox="-0.0498162 -8.34882 23.9179 8.98582" width="23.9179pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M512 -3V55L134 254V256L512 456V514L75 281V230L512 -3Z"></path></g><g transform="matrix(.013,0,0,-0.013,11.263,0)"><path d="M447 623H65C61 580 56 530 47 475H76C100 541 106 550 172 550H388C308 376 196 170 91 -1L98 -12L172 -2C268 204 360 408 455 611L447 623Z"></path></g><g transform="matrix(.013,0,0,-0.013,17.505,0)"><path d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z"></path></g></svg> years old) and Group 2 (AGE <svg height="9.46863pt" id="M365" style="vertical-align:-1.11981pt" version="1.1" viewbox="-0.0498162 -8.34882 23.9179 9.46863" width="23.9179pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M531 285V335L57 550V494L473 310L57 127V71L531 285ZM531 -40V10H57V-40H531Z"></path></g><g transform="matrix(.013,0,0,-0.013,11.263,0)"><path d="M447 623H65C61 580 56 530 47 475H76C100 541 106 550 172 550H388C308 376 196 170 91 -1L98 -12L172 -2C268 204 360 408 455 611L447 623Z"></path></g><g transform="matrix(.013,0,0,-0.013,17.505,0)"><path d="M456 178V225H360V632H320C217 496 115 347 20 206V178H280V106C280 40 276 34 189 27V0H445V27C364 34 360 39 360 106V178H456ZM280 225H82C149 335 214 431 278 520H280V225Z"></path></g></svg> years old).</div>

International Journal of Mathematics and Mathematical Sciences

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Figure 3

Figure 3: Gaussian Copula Regression Modeling for Marker Classification Metrics with Competing Risk Outcomes 