Effect-Size Estimation Using Semiparametric Hierarchical Mixture Models in Disease-Association Studies with Neuroimaging Data

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static.hindawi.com/articles/cmmm/volume-2020/7482403/figures/7482403.fig.001a.svgz" name="7482403.fig.001a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Strong dependency: <svg height="12.522pt" id="M209" style="vertical-align:-3.23367pt" version="1.1" viewbox="-0.0498162 -9.28833 87.1694 12.522" width="87.1694pt" 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="M498 369C498 423 469 454 440 454C415 454 388 432 388 408C388 398 391 390 395 384C401 375 413 354 413 330C413 269 332 132 280 70H278C285 133 286 231 273 319C259 412 231 454 191 454C147 454 85 416 21 322L49 293C91 339 110 351 119 351C129 351 132 349 142 324C181 225 194 56 178 -19C148 -80 115 -167 107 -224L125 -246C167 -243 241 -219 265 -202C260 -169 255 -95 256 -21C261 -11 268 2 323 70C438 212 498 291 498 369Z"></path></g><g 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type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Intermediate dependency: <svg height="12.522pt" id="M210" style="vertical-align:-3.23367pt" version="1.1" viewbox="-0.0498162 -9.28833 87.1694 12.522" width="87.1694pt" 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="M498 369C498 423 469 454 440 454C415 454 388 432 388 408C388 398 391 390 395 384C401 375 413 354 413 330C413 269 332 132 280 70H278C285 133 286 231 273 319C259 412 231 454 191 454C147 454 85 416 21 322L49 293C91 339 110 351 119 351C129 351 132 349 142 324C181 225 194 56 178 -19C148 -80 115 -167 107 -224L125 -246C167 -243 241 -219 265 -202C260 -169 255 -95 256 -21C261 -11 268 2 323 70C438 212 498 291 498 369Z"></path></g><g transform="matrix(.013,0,0,-0.013,10.404,0)"><path d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"></path></g><g transform="matrix(.013,0,0,-0.013,21.667,0)"><path d="M300 -147C201 -63 143 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<div>Average bias in estimating effect sizes for each of the top 500 voxels across 100 simulations when the sample size n is 50 (left), 100 (center), and 200 (right). Panels (a), (b), and (c) represent scenarios with various degrees of dependency among contiguous voxels specified by the parameter <i>γ</i> of the Ising model when the proportion of disease-associated voxels is 20%.</div>

Computational and Mathematical Methods in Medicine

fig1

Figure 1

Figure 1: Effect-Size Estimation Using Semiparametric Hierarchical Mixture Models in Disease-Association Studies with Neuroimaging Data 