--- title: "Statistical framework" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{OmicsBraid statistical framework} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r setup, include=FALSE} knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE) ``` ## Layer-specific effects For entity $j$ across $K$ ordered molecular layers, OmicsBraid estimates a standardized effect vector $$\boldsymbol{\delta}_j=(\delta_{j1},\ldots,\delta_{jK})^T,$$ using Hedges' g and its sampling uncertainty within each layer. ## Matched-subject covariance When the same biological subjects contribute to multiple omic layers, layer-specific estimators are dependent. OmicsBraid estimates cross-layer correlation by stratified matched-subject bootstrap and forms $$V=D_{SE}R_{bootstrap}D_{SE}.$$ ## GLS consensus The covariance-aware common effect is $$\hat\theta=\frac{\mathbf{1}^TV^{-1}\boldsymbol{\delta}}{\mathbf{1}^TV^{-1}\mathbf{1}}.$$ This is a summary of the common component, not a substitute for multivariate evidence. ## Omnibus test The omnibus question is whether the entire effect vector is zero. This remains informative when opposite signs cancel in a pooled signed effect. ## Cross-omic heterogeneity OmicsBraid evaluates deviation from the fitted common effect with $$Q_{omics}=(\boldsymbol{\delta}-\hat\theta\mathbf{1})^TV^{-1}(\boldsymbol{\delta}-\hat\theta\mathbf{1}).$$ The accompanying I2-like quantity is descriptive; v0.2.2 does not impose universal low/moderate/high cutoffs. ## Practical equivalence TOST tests are used to support practical equivalence relative to a scientifically chosen smallest effect size of interest. A conventional $p>0.05$ is not treated as evidence of equivalence. ## Ordered trajectory For a prespecified layer index $L$, the covariance-aware trend model is $$\boldsymbol{\delta}=\beta_0+\beta_1L+\epsilon,\qquad \epsilon\sim N(0,V).$$ Attenuation/amplification require same-direction geometry plus a meaningful, supported ordered trend relative to the user-specified trajectory margin.