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Ultra-High Dimensional Quantile Regression for Longitudinal Data: An Application to Blood Pressure Analysis
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| Pengarang | : | Tianhai Zu |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 97-108 |
| Abstrak | : | Despite major advances in research and treatment, identifying important genotype risk factors for high blood pressure remains challenging. Traditional genome-wide association studies (GWAS) focus on one single nucleotide polymorphism (SNP) at a time. We aim to select among over half a million SNPs along with time-varying phenotype variables via simultaneous modeling and variable selection, focusing on the most dangerous blood pressure levels at high quantiles. Taking advantage of rich data from a large-scale public health study, we develop and apply a novel quantile penalized generalized estimating equations (GEE) approach, incorporating several key aspects including ultra-high dimensional genetic SNPs, the longitudinal nature of blood pressure measurements, time-varying covariates, and conditional high quantiles of blood pressure. Importantly, we identify interesting new SNPs for high blood pressure. Besides, we find blood pressure levels are likely heterogeneous, where the important risk factors identified differ among quantiles. This comprehensive picture of conditional quantiles of blood pressure can allow more insights and targeted treatments. We provide an efficient computational algorithm and prove consistency, asymptotic normality, and the oracle property for the quantile penalized GEE estimators with ultra-high dimensional predictors. Moreover, we establish model-selection consistency for high-dimensional BIC. Simulation studies show the promise of the proposed approach. Supplementary materials for this article are available online. |
Interpolating Population Distributions using Public-Use Data: An Application to Income Segregation using American Community Survey Data
| Pengarang | : | Matthew Simpson |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 84-96 |
| Abstrak | : | The presence of income inequality is an important problem to demographers, policy makers, economists, and social scientists. A causal link has been hypothesized between income inequality and income segregation, which measures how much households with similar incomes cluster. The information theory index is used to measure income segregation, however, critics have suggested the divergence index instead. Motivated by this, we construct both indices using American Community Survey (ACS) estimates of features of the income distribution. Since the elimination of the decennial census long form, methods of computing these indices must be updated to interpolate ACS estimates and account for survey error. We propose a novel model-based method to do this which improves on previous approaches by using more types of estimates, and by providing uncertainty quantification. We apply this method to estimate U.S. census tract-level income distributions, and in turn use these to construct both income segregation indices. We find major differences between the two indices and find evidence that the information index underestimates the relationship between income inequality and income segregation. The literature suggests interventions designed to reduce income inequality by reducing income segregation, or vice versa, so using the information index implicitly understates the value of these interventions. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement. |
Crop Yield Prediction Using Bayesian Spatially Varying Coefficient Models with Functional Predictors
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 70-83 |
| Abstrak | : | Reliable prediction for crop yield is crucial for economic planning, food security monitoring, and agricultural risk management. This study aims to develop a crop yield forecasting model at large spatial scales using meteorological variables closely related to crop growth. The influence of climate patterns on agricultural productivity can be spatially inhomogeneous due to local soil and environmental conditions. We propose a Bayesian spatially varying functional model (BSVFM) to predict county-level corn yield for five Midwestern states, based on annual precipitation and daily maximum and minimum temperature trajectories modeled as multivariate functional predictors. The proposed model accommodates spatial correlation and measurement errors of functional predictors, and respects the spatially heterogeneous relationship between the response and associated predictors by allowing the functional coefficients to vary over space. The model also incorporates a Bayesian variable selection device to further expand its capacity to accommodate spatial heterogeneity. The proposed method is demonstrated to outperform other highly competitive methods in corn yield prediction, owing to the flexibility of allowing spatial heterogeneity with spatially varying coefficients in our model. Our study provides further insights into understanding the impact of climate change on crop yield. Supplementary materials for this article are available online. |
Capture-Recapture Models with Heterogeneous Temporary Emigration
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 56-69 |
| Abstrak | : | We propose a novel approach for modeling capture-recapture (CR) data on open populations that exhibit temporary emigration, while also accounting for individual heterogeneity to allow for differences in visit patterns and capture probabilities between individuals. Our modeling approach combines changepoint processes—fitted using an adaptive approach—for inferring individual visits, with Bayesian mixture modeling—fitted using a nonparametric approach—for identifying clusters of individuals with similar visit patterns or capture probabilities. The proposed method is extremely flexible as it can be applied to any CR dataset and is not reliant upon specialized sampling schemes, such as Pollock’s robust design. We fit the new model to motivating data on salmon anglers collected annually at the Gaula river in Norway. Our results when analyzing data from the 2017, 2018, and 2019 seasons reveal two clusters of anglers—consistent across years—with substantially different visit patterns. Most anglers are allocated to the “occasional visitors” cluster, making infrequent and shorter visits with mean total length of stay at the river of around seven days, whereas there also exists a small cluster of “super visitors,” with regular and longer visits, with mean total length of stay of around 30 days in a season. Our estimate of the probability of catching salmon whilst at the river is more than three times higher than that obtained when using a model that does not account for temporary emigration, giving us a better understanding of the impact of fishing at the river. Finally, we discuss the effect of the COVID-19 pandemic on the angling population by modeling data from the 2020 season. Supplementary materials for this article are available online. |
iProMix: A Mixture Model for Studying the Function of ACE2 based on Bulk Proteogenomic Data
| Pengarang | : | Xiaoyu Song |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 43-55 |
| Abstrak | : | Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over six million deaths in the ongoing COVID-19 pandemic. SARS-CoV-2 uses ACE2 protein to enter human cells, raising a pressing need to characterize proteins/pathways interacted with ACE2. Large-scale proteomic profiling technology is not mature at single-cell resolution to examine the protein activities in disease-relevant cell types. We propose iProMix, a novel statistical framework to identify epithelial-cell specific associations between ACE2 and other proteins/pathways with bulk proteomic data. iProMix decomposes the data and models cell type-specific conditional joint distribution of proteins through a mixture model. It improves cell-type composition estimation from prior input, and uses a nonparametric inference framework to account for uncertainty of cell-type proportion estimates in hypothesis test. Simulations demonstrate iProMix has well-controlled false discovery rates and favorable powers in nonasymptotic settings. We apply iProMix to the proteomic data of 110 (tumor-adjacent) normal lung tissue samples from the Clinical Proteomic Tumor Analysis Consortium lung adenocarcinoma study, and identify interferon ????/???? response pathways as the most significant pathways associated with ACE2 protein abundances in epithelial cells. Strikingly, the association direction is sex-specific. This result casts light on the sex difference of COVID-19 incidences and outcomes, and motivates sex-specific evaluation for interferon therapies. Supplementary materials for this article are available online. |
A Generalized Integration Approach to Association Analysis with Multi-category Outcome: An Application to a Tumor Sequencing Study of Colorectal Cancer and Smoking
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 29-42 |
| Abstrak | : | Cancer is a heterogeneous disease, and rapid progress in sequencing and -omics technologies has enabled researchers to characterize tumors comprehensively. This has stimulated an intensive interest in studying how risk factors are associated with various tumor heterogeneous features. The Cancer Prevention Study-II (CPS-II) cohort is one of the largest prospective studies, particularly valuable for elucidating associations between cancer and risk factors. In this article, we investigate the association of smoking with novel colorectal tumor markers obtained from targeted sequencing. However, due to cost and logistic difficulties, only a limited number of tumors can be assayed, which limits our capability for studying these associations. Meanwhile, there are extensive studies for assessing the association of smoking with overall cancer risk and established colorectal tumor markers. Importantly, such summary information is readily available from the literature. By linking this summary information to parameters of interest with proper constraints, we develop a generalized integration approach for polytomous logistic regression model with outcome characterized by tumor features. The proposed approach gains the efficiency through maximizing the joint likelihood of individual-level tumor data and external summary information under the constraints that narrow the parameter searching space. We apply the proposed method to the CPS-II data and identify the association of smoking with colorectal cancer risk differing by the mutational status of APC and RNF43 genes, neither of which is identified by the conventional analysis of CPS-II individual data only. These results help better understand the role of smoking in the etiology of colorectal cancer. Supplementary materials for this article are available online. |
LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures
| Pengarang | : | Zhengwu Zhang |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 118 (No. 541) |
| Halaman | : | 3-17 |
| Abstrak | : | Over the past 30 years, magnetic resonance imaging has become a ubiquitous tool for accurately visualizing the change and development of the brain’s subcortical structures (e.g., hippocampus). Although subcortical structures act as information hubs of the nervous system, their quantification is still in its infancy due to many challenges in shape extraction, representation, and modeling. Here, we develop a simple and efficient framework of longitudinal elastic shape analysis (LESA) for subcortical structures. Integrating ideas from elastic shape analysis of static surfaces and statistical modeling of sparse longitudinal data, LESA provides a set of tools for systematically quantifying changes of longitudinal subcortical surface shapes from raw structure MRI data. The key novelties of LESA include: (i) it can efficiently represent complex subcortical structures using a small number of basis functions and (ii) it can accurately delineate the spatiotemporal shape changes of the human subcortical structures. We applied LESA to analyze three longitudinal neuroimaging datasets and showcase its wide applications in estimating continuous shape trajectories, building life-span growth patterns, and comparing shape differences among different groups. In particular, with the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we found that Alzheimer’s Disease (AD) can significantly speed the shape change of the lateral ventricle and the hippocampus from 60 to 75 years olds compared with normal aging. Supplementary materials for this article are available online. |
Ahimsa Dalam Pandangan Mahatma Gandhi
| Pengarang | : | Toni Santosa |
| Nama Majalah/Jurnal | : | Praba |
| Volume / Edisi | : | XXXIX (No. 1) |
| Halaman | : | 45-58 |
| Abstrak | : | Abstrak tidak tersedia. |
MUHAMMAD YAMIN: UPAYA MENYATUKAN BENANG-BENANG KEANEKAAN DALAM SAMPUL PERSATUAN
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Respons : Jurnal Etika Sosial |
| Volume / Edisi | : | 18 (No. 1) |
| Halaman | : | 117-148 |
| Abstrak | : | Muhammad Yamin adalah seorang tokoh nasional yang bersama Soeka- rno dan Mohamad Hatta berjuang melahirkan Republik Indonesia. Yamin dengan latar belakangnya sebagai penyair dan ahli hukum telah lama mencita-citakan Indo- nesia, yang terdiri atas berbagai keanearagaman menjadi negara merdeka dan ber- satu. Kesatuan Indonesia diyakini Yamin sebagai nasib yang sudah ditentukan sejak awal bagi bangsa Indonesia. Bagi Yamin keindonesiaan merupakan kehendak untuk hidup bersama mengatasi segala perbedaan-perbedaan yang ada. Romantisme sebagai penyair memandang fakta perbedaan sebagai sesuatu yang indah dan dapat dikelola menjadi kehidupan bersama yang harmonis dalam persatuan sebagai bangsa. Ide per- satuan Yamin diawalinya dengan menegaskan perlunya satu bahasa yang menjadi ba- hasa persatuan sebagai jembatan yang bisa menghubungkan keanekaragaman dengan demikian berbagai keragaman dan perbedaan dapat dikomunikasikan denganbaik. Ide Unitarisme diolah oleh Yamin sehingga unitarisme Yamin bukan sekedar konsep politik namun yang lebih kuat dari itu gagasan ini merupakan konsep budaya yang kelak diharapkan mampu membentuk kesatuan karakter. |
NEGARA UNTUK RAKYAT DAN RAKYAT UNTUK NEGARA
| Pengarang | : | Ristyantoro, Rodemeus |
| Nama Majalah/Jurnal | : | Respons : Jurnal Etika Sosial |
| Volume / Edisi | : | 18 (No. 1) |
| Halaman | : | 91-115 |
| Abstrak | : | Paham Negara integralistik Soepomo seringkali disalahpahami. Ada yang menganggap paham ini mengarah ke totaliter, di mana penguasa bisa bersikap sewenang-wenang. Ada juga yang menganggap paham ini anti-demokrasi. Pandangan seperti itu bisa saja muncul jika kita tidak begitu menyelami pandangan Soepomo se- cara utuh. Pada intinya, Socpomo ingin menawarkan sesuatu yang sesuai dengan pa- ham ketimuran dan menolak faham Barat yang pada waktu itu memang sedang diper- angi. Jadi, sebenarnya, inti paham Negara integralistik adalah menyatunya pemimpin dengan rakyat, Jika ada kesatuan tentunya keinginan-keinginan dari kedua belah pihak tidak akan saling menyimpang. Mereka akan saling melengkapi sebab pemimpin dan rakyat merupakan satu-kesatuan organik. Itulah inti dari semangat manunggaling kawulo gusti. Sementara itu, penolakan demokrasi di sini terutama demokrasi Barat, karena demokrasi Barat bersifat liberal, individualistik. Masyarakat Indonesia itu tidak individualistik, melainkan berdasarkan pada rasa bersama, kolektif. Bentuk negara In- donesia harus mengungkapkan "semangat kebatinan bangsa Indonesia", yaitu hasrat rakyat akan persatuan: persatuan hidup, persatuan antara dunia luar dan batin, antara rakyat dan para pemimpinnya. |