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Determinan Indeks Massa Tubuh Remaja Putri Di Kota Bukit Tinggi, Tahun 2006, Rini Santy

Kesmas

Di Indonesia, pada 1999-2003, remaja putri yang mengalami Kekurangan EnergiKronis (KEK). akibat asupan energi yang kurang adalah 35–40% dan sekitar 50% remaja putri menderita status gizi kurang (IMT <18,5 kg/m² ). Tujuan penelitian adalah mengetahui gambaran epidemiologi. IMT remaja putri dan berbagai faktor yang berhubungan Rancangan studi yang digunakan adalah rancangan potong lintang (cross sectional). Populasi adalah remaja putri berusia 16-18 tahun yang tinggal di Buki Tinggi dan sampel adalah 156 siswi kelas III SLTA (SMA, MA, dan SMK) usia 16–18 tahun yang terpilih dari 11 sekola yang diamati. Analisis data dilakukan secara multivariate dengan metoda logistic regression ganda. Hasil penelitian (1) Rata-rata IMT remja putri adalah 20,69 kg/m²± 2,63. (2) Proporsi siswi dengan IMT<18,5 kg/m² adalah 19,9% yang meliputi 14,1% kekurangan gizi ringan dan 5,8% kekurangan gizi berat. (3) Rata-rata asupan energi remaja putri adalah 1,694 kalori dan rata-rata kontribusi terhadap total energi protein (11,8%), lemak (26,7%) dan karbohidrat (58,7%). (4) Rata-rata asupan energi dibanding AKG meliputi total energi (77%), protein (93,6%). Variabel yang berhubungan secara bermakna dengan IMP pada remaja meliputi total energi, kebiasaan makan dan citra tubuh dengan IMT remaja putri dengan variabel utama adalah total energi. In Indonesia, in period of 1999–2003, abot 35–40% women in productive age of 15–19 are at risk of Chronic Energy Deficiency (KEK) because of insufficient consumption of energy. This research is aimed at obtaining the description of nutritional status of girls in Bukittinggi and factors related to it. The research that was conductec in period of February tol March 2006 used the design of cross sectional. The study population is the girls studied are represented by the third-grade female students of senior high schools of 16–18 who are categorized as a late teenager who is very close to pregnant period. The sample consist of 156 female student that was selected by systematic random sampling at 11 schools. The results show that the BMI of the girls is 20.69 kg/m²± 2.63 on average. The proportion of students having BMI <18.5 kg/m2 is 19.9% all of which is distributed to 14.1% of light level of malnutrition and 5.8% for heavy level of malnutrition. Intake per day is 1,694 calorie on average with protein contributed to intake is 11.8%, fat 26.7% dan carbohydrat 58.7%. Intake energy compared with Recommended Dietary Allowence (RDA) are total energy consumption 77%, protein 93.6%, lemak 65.3% and carbohydrat 84.7%. There is a significant relation between energy consumption, eating habit, body image, by BMI. Variable energy consumption is the dominant variable influencing BMI.

Hubungan Pertambahan Berat Badan Selama Kehamilan Dengan Berat Lahir Bayi Di Sukaraja Bogor Tahun 2001- 2003, Elmy Rindang Turhayati

Kesmas

Di Indonesia, pertambahan berat badan selama kehamilan umumnya rendah (<10 kg), padahal pertambahan berat badan tersebut merupakan indikator pertubuhan janin yang penting. Di Kabupaten Bogor, prevalensi ibu hamil penderita Kurang Energi Kronis (27,6%) adalah tinggi. Penelitian ini bertujuan mengetahui pertambahan berat badan selama kehamilan dan hubungannya dengan berat badan bayi baru lahir. Penelitian dengan disain potong lintang ini dilakukan pada 270 sampel ibu hamil yang melahirkan cukup bulan (>37 minggu), mengunakan metoda Regresi Logistik. Ditemukan proporsi bayi lahir dengan berat 2.500-2.999 gram adalah 47,8%. Rata-rata berat lahir adalah 3.015 gram. Proporsi ibu dengan pertambahan berat badan selama kehamilan 48,9%. Rata-rata pertambahan berat badan selama kehamilan sebesar 9,1 kg. Variabel yang berhubungan secara bermakna bermakna dengan berat lahir adalah pertambahan berat badan selama kehamilan (nilai p = 0,000, OR = 7,28, CI 95%= 4,25-1,46), dan asupan energi (nilai p = 0,000, OR = 5,15, CI 95% = 2,976-8,913). Juga ditemukan interaksi antara asupan energi dengan pertambahan berat badan selama …

Modeling The Incubation Period Of Anthrax, Ron Brookmeyer, Elizabeth Johnson, Sarah Barry

Ron Brookmeyer

Models of the incubation period of anthrax are important to public health planners because they can be used to predict the delay before outbreaks are detected, the size of an outbreak and the duration of time that persons should remain on antibiotics to prevent disease. The difficulty is that there is little direct data about the incubation period in humans. The objective of this paper is to develop and apply models for the incubation period of anthrax. Mechanistic models that account for the biology of spore clearance and germination are developed based on a competing risks formulation. The models predict …

Lehmann Family Of Roc Curves, Mithat Gonen, Glenn Heller

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

Receiver operating characteristic (ROC) curves are useful in evaluating the ability of a continuous marker in discriminating between the two states of a binary outcome such as diseased/not diseased. The most popular parametric model for an ROC curve is the binormal model which assumes that the marker is normally distributed conditional on the outcome. Here we present an alternative to the binormal model based on the Lehmann family, also known as the proportional hazards specification. The resulting ROC curve and its functionals (such as the area under the curve) have simple analytic forms. We derive closed-form expressions for the asymptotic …

A Likelihood Based Method For Real Time Estimation Of The Serial Interval And Reproductive Number Of An Epidemic, Laura Forsberg White, Marcello Pagano

Harvard University Biostatistics Working Paper Series

No abstract provided.

A Note On Empirical Likelihood Inference Of Residual Life Regression, Ying Qing Chen, Yichuan Zhao

Yichuan Zhao

Mean residual life function, or life expectancy, is an important function to characterize distribution of residual life. The proportional mean residual life model by Oakes and Dasu (1990) is a regression tool to study the association between life expectancy and its associated covariates. Although semiparametric inference procedures have been proposed in the literature, the accuracy of such procedures may be low when the censoring proportion is relatively large. In this paper, the semiparametric inference procedures are studied with an empirical likelihood ratio method. An empirical likelihood confidence region is constructed for the regression parameters. The proposed method is further compared …

Numerical And Asymptotical Study Of Three-Dimensional Wave Packets In A Compressible Boundary Layer, Eric Forgoston, Michael Viergutz, Anatoli Tumin

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

A three-dimensional wave packet generated by a local disturbance in a two-dimensional hypersonic boundary layer flow is studied with the aid of the previously solved initialvalue problem. The solution can be presented as a sum of modes consisting of continuous and discrete spectra of temporal stability theory. Two discrete modes, known as Mode S and Mode F, are of interest in high-speed flows since they may be involved in a laminar-turbulent transition scenario. The continuous and discrete spectra are analyzed numerically for a hypersonic flow. A comprehensive study of the spectrum is performed, including Reynolds number, Mach number and temperature …

A Semiparametric Approach For The Nonparametric Transformation Survival Model With Multiple Covariates, Xiao Song, Shuangge Ma, Jian Huang, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

The nonparametric transformation model for survival time that makes no parametric assumptions on both the transformation function and the error is appealing in its flexibility. The nonparametric transformation model makes no assumption on the forms of the transformation function and the error distribution. This model is appealing in its flexibility for modeling censored survival data. Current approaches for estimation of the regression parameters involve maximizing discontinuous objective functions, which are numerically infeasible to implement in the case of multiple covariates. Based on the partial rank estimator (Khan & Tamer, 2004), we propose a smoothed partial rank estimator which maximizes a …

Life Data Analysis Of Repairable Systems: A Case Study On Brigham Young University Media Rooms, Stephen Oluaku Manortey

Theses and Dissertations

It is an undisputable fact that most systems, upon consistence usage are bound to fail in the performance of their intended functions at a point in time. When this occurs, various strategies are set in place to restore them back to a satisfactory performance. This may include replacing the failed component with a new one, swapping parts, resetting adjustable parts to mention but a few. Any such system is referred to as a repairable system. There is the need to study these systems and use statistical models to predict their failing time and be able to set modalities in place …

Wavelet-Based Functional Mixed Models To Characterize Population Heterogeneity In Accelerometer Profiles: A Case Study. , Jeffrey S. Morris, Cassandra Arroyo, Brent A. Coull, Louise M. Ryan, Steven L. Gortmaker

Jeffrey S. Morris

We present a case study illustrating the challenges of analyzing accelerometer data taken from a sample of children participating in an intervention study designed to increase physical activity. An accelerometer is a small device worn on the hip that records the minute-by-minute activity levels of the child throughout the day for each day it is worn. The resulting data are irregular functions characterized by many peaks representing short bursts of intense activity. We model these data using the wavelet-based functional mixed model. This approach incorporates multiple fixed effects and random effect functions of arbitrary form, the estimates of which are …

Alternative Probeset Definitions For Combining Microarray Data Across Studies Using Different Versions Of Affymetrix Oligonucleotide Arrays, Jeffrey S. Morris, Chunlei Wu, Kevin R. Coombes, Keith A. Baggerly, Jing Wang, Li Zhang

Jeffrey S. Morris

Many published microarray studies have small to moderate sample sizes, and thus have low statistical power to detect significant relationships between gene expression levels and outcomes of interest. By pooling data across multiple studies, however, we can gain power, enabling us to detect new relationships. This type of pooling is complicated by the fact that gene expression measurements from different microarray platforms are not directly comparable. In this chapter, we discuss two methods for combining information across different versions of Affymetrix oligonucleotide arrays. Each involves a new approach for combining probes on the array into probesets. The first approach involves …

An Econometric Method Of Correcting For Unit Nonresponse Bias In Surveys, Martin Ravallion, Anton Korinek, Johan Mistiaen

Martin Ravallion

Past approaches to correcting for unit nonresponse in sample surveys by re-weighting the data assume that the problem is ignorable within arbitrary subgroups of the population. Theory and evidence suggest that this assumption is unlikely to hold, and that household characteristics such as income systematically affect survey compliance. We show that this leaves a bias in the re-weighted data and we propose a method of correcting for this bias. The geographic structure of nonresponse rates allows us to identify a micro compliance function, which is then used to re-weight the unit-record data. An example is given for the US Current …

Identifying Important Explanatory Variables For Time-Varying Outcomes., Oliver Bembom, Maya L. Petersen, Mark J. Van Der Laan

Maya Petersen

This chapter describes a systematic and targeted approach for estimating the impact of each of a large number of baseline covariates on an outcome that is measured repeatedly over time. These variable importance estimates can be adjusted for a user-specified set of confounders and lend themselves in a straightforward way to obtaining confidence intervals and p-values. Hence, they can in particular be used to identify a subset of baseline covariates that are the most important explanatory variables for the time-varying outcome of interest. We illustrate the methodology in a data analysis aimed at finding mutations of the human immunodeficiency virus …

Identifying Important Explanatory Variables For Time-Varying Outcomes., Oliver Bembom, Maya L. Petersen, Mark J. Van Der Laan

Oliver Bembom

This chapter describes a systematic and targeted approach for estimating the impact of each of a large number of baseline covariates on an outcome that is measured repeatedly over time. These variable importance estimates can be adjusted for a user-specified set of confounders and lend themselves in a straightforward way to obtaining confidence intervals and p-values. Hence, they can in particular be used to identify a subset of baseline covariates that are the most important explanatory variables for the time-varying outcome of interest. We illustrate the methodology in a data analysis aimed at finding mutations of the human immunodeficiency virus …

Gamma Shape Mixtures For Heavy-Tailed Distributions, Sergio Venturini, Francesca Dominici, Giovanni Parmigiani

Johns Hopkins University, Dept. of Biostatistics Working Papers

An important question in health services research is the estimation of the proportion of medical expenditures that exceed a given threshold. Typically, medical expenditures present highly skewed, heavy tailed distributions, for which a) simple variable transformations are insufficient to achieve a tractable low- dimensional parametric form and b) nonparametric methods are not efficient in estimating exceedance probabilities for large thresholds. Motivated by this context, in this paper we propose a general Bayesian approach for the estimation of tail probabilities of heavy-tailed distributions,based on a mixture of gamma distributions in which the mixing occurs over the shape parameter. This family provides …

New Tests Of Univariate Symmetry Based On The Gini Mean Difference, Hend Ouda

Dissertations

Gini mean difference (GMD) was proposed as a measure of income inequality by Corrado Gini in 1912. Since then it has been widely applied - mostly in theeconomics, but also in statistical and social science research.

Four statistical tests of univariate symmetry are being proposed---all based on the comparison of variation below and above the median (known or estimated) measured by the GMD. These tests are applicable to the data from populations with median known and unknown, and each of them has its rank-basedcounterpart, so they can also be used for ordinal data.

A Monte Carlo simulation study was performed …

Topology Of Attractors From Two-Piece Expanding Maps, Youngna Choi

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

In this paper we study the topology of the invariant sets derived from two-piece expanding maps. We classify the conditions under which the invariant sets are topological attractors, and show that the set of attractors is open and dense in the set of invariant sets derived by two-piece expanding maps.

Modeling An Outbreak Of Anthrax, Ron Brookmeyer

Ron Brookmeyer

Introduction

On October 2, 2001 a sixty-three-year-old Florida man who worked as a photo editor at a media publishing company was admitted to an emergency department complaining of nausea, vomiting, and fever. His symptoms began four days earlier on a recreational trip to North Carolina. The man died shortly thereafter. An astute clinician quickly made the surprising diagnosis of inhalational anthrax, which is a serious and deadly disease. The diagnosis was surprising because inhalational anthrax is extremely rare; only 18 cases were reported in the United States between 1900 and 1978. Public health officials at first believed that the Florida …

Optimizing The Expected Overlap Of Survey Samples Via The Northwest Corner Rule, Lenka Mach, Philip T. Reiss, Ioana Schiopu-Kratina

Philip T. Reiss

In survey sampling there is often a need to coordinate the selection of pairs of samples drawn from two overlapping populations so as to maximize or minimize their expected overlap, subject to constraints on the marginal probabilities determined by the respective designs. For instance, maximizing the expected overlap between repeated samples can stabilize the resulting estimates of change and reduce the costs of first contacts; minimizing the expected overlap can avoid overburdening respondents with multiple surveys. We focus on the important special case in which both samples are selected by simple random sampling without replacement (SRSWOR) conducted independently within each …

Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh

The University of Michigan Department of Biostatistics Working Paper Series

SUMMARY. We consider a semiparametric regression model that relates a normal outcome to covariates and a genetic pathway, where the covariate effects are modeled parametrically and the pathway effect of multiple gene expressions is modeled parametrically or nonparametrically using least squares kernel machines (LSKMs). This unified framework allows a flexible function for the joint effect of multiple genes within a pathway by specifying a kernel function and allows for the possibility that each gene expression effect might be nonlinear and the genes within the same pathway are likely to interact with each other in a complicated way. This semiparametric model …

Spatio-Temporal Analysis Of Areal Data And Discovery Of Neighborhood Relationships In Conditionally Autoregressive Models, Subharup Guha, Louise Ryan

Harvard University Biostatistics Working Paper Series

No abstract provided.

Semiparametric Regression Of Multi-Dimensional Genetic Pathway Data: Least Squares Kernel Machines And Linear Mixed Models, Dawei Liu, Xihong Lin, Debashis Ghosh

Harvard University Biostatistics Working Paper Series

No abstract provided.

Analysis Of Case-Control Age-At-Onset Data Using A Modified Case-Cohort Method, Bin Nan, Xihong Lin

The University of Michigan Department of Biostatistics Working Paper Series

Case-control designs are widely used in rare disease studies. In a typical case-control study, data are collected from a sample of all available subjects who have experienced a disease (cases) and a sub-sample of subjects who have not experienced the disease (controls) in a study cohort. Cases are often oversampled in case-control studies. Logistic regression is a common tool to estimate the relative risks of the disease and a set of covariates. Very often in such a study, information of ages-at-onset of the disease for all cases and ages at survey of controls are known. Standard logistic regression analysis using …

A Comparison Of Microarray Analyses: A Mixed Models Approach Versus The Significance Analysis Of Microarrays, Nathan Wallace Stephens

Theses and Dissertations

DNA microarrays are a relatively new technology for assessing the expression levels of thousands of genes simultaneously. Researchers hope to find genes that are differentially expressed by hybridizing cDNA from known treatment sources with various genes spotted on the microarrays. The large number of tests involved in analyzing microarrays has raised new questions in multiple testing. Several approaches for identifying differentially expressed genes have been proposed. This paper considers two: (1) a mixed models approach, and (2) the Signiffcance Analysis of Microarrays.

Gene Expression Patterns That Predict Sensitivity To Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors In Lung Cancer Cell Lines And Human Lung Tumors, Justin M. Balko, Anil Potti, Christopher Saunders, Arnold J. Stromberg, Eric B. Haura, Esther P. Black

Statistics Faculty Publications

BACKGROUND: Increased focus surrounds identifying patients with advanced non-small cell lung cancer (NSCLC) who will benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI). EGFR mutation, gene copy number, coexpression of ErbB proteins and ligands, and epithelial to mesenchymal transition markers all correlate with EGFR TKI sensitivity, and while prediction of sensitivity using any one of the markers does identify responders, individual markers do not encompass all potential responders due to high levels of inter-patient and inter-tumor variability. We hypothesized that a multivariate predictor of EGFR TKI sensitivity based on gene expression data would offer a …

Smoothed Rank Regression With Censored Data, Glenn Heller

Memorial Sloan-Kettering Cancer Center, Dept. of Epidemiology & Biostatistics Working Paper Series

A weighted rank estimating function is proposed to estimate the regression parameter vector in an accelerated failure time model with right censored data. In general, rank estimating functions are discontinuous in the regression parameter, creating difficulties in determining the asymptotic distribution of the estimator. A local distribution function is used to create a rank based estimating function that is continuous and monotone in the regression parameter vector. A weight is included in the estimating function to produce a bounded influence estimate. The asymptotic distribution of the regression estimator is developed and simulations are performed to examine its finite sample properties. …

Properties Of Monotonic Effects, Tyler J. Vanderweele, James M. Robins

COBRA Preprint Series

Various relationships are shown hold between monotonic effects and weak monotonic effects and the monotonicity of certain conditional expectations. This relationship is considered for both binary and non-binary variables. Counterexamples are provide to show that the results do not hold under less restrictive conditions. The ideas of monotonic effects are furthermore used to relate signed edges on a directed acyclic graph to qualitative effect modification.

Multiple Testing With An Empirical Alternative Hypothesis, James E. Signorovitch

Harvard University Biostatistics Working Paper Series

An optimal multiple testing procedure is identified for linear hypotheses under the general linear model, maximizing the expected number of false null hypotheses rejected at any significance level. The optimal procedure depends on the unknown data-generating distribution, but can be consistently estimated. Drawing information together across many hypotheses, the estimated optimal procedure provides an empirical alternative hypothesis by adapting to underlying patterns of departure from the null. Proposed multiple testing procedures based on the empirical alternative are evaluated through simulations and an application to gene expression microarray data. Compared to a standard multiple testing procedure, it is not unusual for …

Doubly Penalized Buckley-James Method For Survival Data With High-Dimensional Covariates, Sijian Wang, Bin Nan, Ji Zhu, David G. Beer

The University of Michigan Department of Biostatistics Working Paper Series

Recent interest in cancer research focuses on predicting patients' survival by investigating gene expression profiles based on microarray analysis. We propose a doubly penalized Buckley-James method for the semiparametric accelerated failure time model to relate high-dimensional genomic data to censored survival outcomes, which uses a mixture of L₁-norm and L₂-norm penalties. Similar to the elastic-net method for linear regression model with uncensored data, the proposed method performs automatic gene selection and parameter estimation, where highly correlated genes are able to be selected (or removed) together. The two-dimensional tuning parameter is determined by cross-validation and uniform design. …

Ex Ante Choices Of Law And Forum: An Empirical Analysis Of Corporate Merger Agreements, Theodore Eisenberg, Geoffrey P. Miller

Cornell Law Faculty Publications

Legal scholars have focused much attention on the incorporation puzzle—why business corporations so heavily favor Delaware as the site of incorporation. This paper suggests that the focus on the incorporation decision overlooks a broader but intimately related set of questions. The choice of Delaware as a situs of incorporation is, effectively, a choice of law decision. A company electing to charter in Delaware selects Delaware law (and authorizes Delaware courts to adjudicate legal disputes) regarding the allocation of governance authority within the firm. In this sense, the incorporation decision is fundamentally similar to any setting in which a company selects …