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STATISTICAL MODELLING Part IIC / Michaelmas 2022Example Sheet 1 ...
www.statslab.cam.ac.uk/~qz280/teaching/modelling-2022/E1.pdf3 Jun 2024: In all the questions that follow, X is an n by p design matrix with full column rank and H is theorthogonal projection on to the column space of X. ... Show that for all x Rn, ‖x‖2 ‖ΠWx‖2 ‖ΠV x‖2. (b) Consider the normal linear model with a -
STATISTICAL MODELLING Part IIC / Michaelmas 2022Example Sheet 3 ...
www.statslab.cam.ac.uk/~qz280/teaching/modelling-2022/E3.pdf3 Jun 2024: f(y; µ,σ2) =1. 2πσ2e. (yµ)2. 2σ2 ,y R. (b) The Gamma distribution, Gamma(α,β):. ... 2 = 2/σ2βj for all j). (c) How do the expressions in (a) and (b) simplify when g(µi) is the canonical link function? -
CAUSAL INFERENCE Part III / Michaelmas 2023Example Sheet 2 ...
www.statslab.cam.ac.uk/~qz280/teaching/causal-2023/E2.pdf3 Jun 2024: j, j) B for all j V) or an directed acyclic graph (DAG) G = (V,D). ... Show that there exists a trek from j to k via U(meaning all its non-endpoints are in U) if and only if there exists an arc from j to -
Confounder Selection via Iterative Graph Expansion Qingyuan Zhao…
www.statslab.cam.ac.uk/~qz280/talk/lse-2024/slides.pdf3 Jun 2024: adjustment set for A, B given S′ in G. Then every element in the output ofConfounderSelect(X, Y ) is a sufficient adjustment set for (X, Y ). 2 Completeness (all minimal primary ... all minimal sufficiency): Suppose further thatFindPrimary((A, B); S′) -
Confounder Selection via (Iterative) Graph Expansion Qingyuan Zhao…
www.statslab.cam.ac.uk/~qz280/talk/pcic-2023/slides.pdf3 Jun 2024: adjustment set for A, B given S′ in G. Then every element in the output ofConfounderSelect(X, Y ) is a sufficient adjustment set for (X, Y ). 2 Completeness (all minimal primary ... all minimal sufficiency): Suppose further thatFindPrimary((A, B); S′) -
MR Data Challenge 2019 — The role of lipoprotein subfractions in…
www.statslab.cam.ac.uk/~qz280/publication/mr-lipids/report.pdf3 Jun 2024: out$pval.sel <- pval.sel. out.all <- rbind(out.all, out)}. 6. Qingyuan Zhao. Qingyuan Zhao. ... library(ggplot2). ggplot(out.all) aes(x = method, y = b, ymin = b - 1.96 se, ymax = b 1.96 se,col = pval.adjusted < 0.05). -
MR Data Challenge 2019 — The role of lipoprotein subfractions in…
www.statslab.cam.ac.uk/~qz280/talk/mr-raps-markdown/report.pdf3 Jun 2024: out$pval.sel <- pval.sel. out.all <- rbind(out.all, out)}. 6. Qingyuan Zhao. Qingyuan Zhao. ... library(ggplot2). ggplot(out.all) aes(x = method, y = b, ymin = b - 1.96 se, ymax = b 1.96 se,col = pval.adjusted < 0.05). -
Mendelian randomization: From genetic association to epidemiological…
www.statslab.cam.ac.uk/~qz280/publication/mr-partially-bayes/slides.pdf3 Jun 2024: year, 31% of all global deaths.1. I Risk factors: hypertension, high cholesterol, smoking,. ... All solutions in B are consistent: β̂APS. p β0 and pτ̂2APS pτ20p 0. -
Will competition-winning methods for causal inference also succeed in …
www.statslab.cam.ac.uk/~qz280/publication/acic-competition-comment/paper.pdf3 Jun 2024: The studies in Cook, Shadishand Wong (2008) and Shadish, Clark and Steiner (2008) are all too rare examplesof what can be learned from “in vivo” investigations. ... Although the three authors of this commentary havedifferent views on how to use -
Towards Reliable Inference for Precision Medicine
www.statslab.cam.ac.uk/~qz280/talk/jsm-2021/slides.pdf3 Jun 2024: Unmeasured confoudnersI Define r1 Γ,δ r2 if V (r2) V (r1) > δ for all distributions in the Γ-sensitivity model. ... 1. What is the ordering of all the ITRs? 2. Which ITRs are among the best?
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