Pre-Eklampsia Berat Dan Kematian Ibu,
2015
Fakultas Kesehatan Masyarakat, Universitas Malahayati, Lampung
Pre-Eklampsia Berat Dan Kematian Ibu, Nova Muhani, Besral Besral
Kesmas
Pre-eklampsia berat, salah satu penyebab utama kematian ibu di Indonesia dan di RSUD Dr. H. Abdul Moeloek Lampung, merupakan penyebab kematian ibu nomor satu (47,25%). Penelitian ini bertujuan untuk mengetahui hubungan prediktor pre-eklampsi berat (PEB) yang dinilai dari tekanan darah sistolik, tekanan darah diastolik, proteiunuria, eklampsia, sindrom hemolysis, elevated liver enzymes, low platelets count (HELLP) dengan kematian ibu di RSUD Dr. H. Abdul Moeloek. Penelitian ini menggunakan desain kasus kontrol dengan jumlah sampel 60 kasus dan 120 kontrol. Data diolah dari rekam medis rumah sakit selama periode lima tahun (2010 – 2014). Hasil penelitian ini memperlihatkan bahwa sindrom HELLP memiliki …
Peran Tenaga Kesehatan Dan Keluarga Dalam Kehamilan Usia Remaja,
2015
Universitas Andalas, Padang
Peran Tenaga Kesehatan Dan Keluarga Dalam Kehamilan Usia Remaja, Mery Ramadani, Dien Gusta Anggraini Nursal, Livia Ramli
Kesmas
Sebanyak 10,3% kematian tidak langsung pada ibu disebabkan kehamilan usia remaja (< 20 tahun). Di Kabupaten Tanah Datar, masih terjadi peningkatan kehamilan usia remaja dalam tiga tahun terakhir. Penelitian ini bertujuan untuk mengetahui peran tenaga kesehatan, dukungan keluarga, dan pengetahuan remaja dengan kehamilan usia remaja di wilayah kerja Puskesmas Singgalang, Kabupaten Tanah Datar tahun 2014. Penelitian dilaksanakan pada bulan Mei – Juni 2014 menggunakan desain potong lintang. Populasi adalah seluruh remaja putri berusia < 20 tahun yang telah menikah berjumlah 215 orang. Sampel berjumlah 68 orang dan pengambilan sampel dilakukan secara proporsional di delapan jorong/desa. Data dikumpulkan melalui wawancara menggunakan kuesioner. Kemudian, analisis bivariat dilakukan dengan uji kai kuadrat dan analisis multivariat dengan uji regresi logistik ganda. Hasil penelitian mendapatkan sebanyak 55,9% responden hamil di usia remaja. Sebanyak 52,9% responden kurang merasakan peran dari tenaga kesehatan, 66,2% kurang mendapat dukungan keluarga, dan 58,8% memiliki pengetahuan rendah. Didapatkan hubungan peran tenaga kesehatan (nilai p = 0,032), dukungan keluarga (nilai p = 0,025), dan tingkat pengetahuan (nilai p = 0,002) dengan kehamilan usia remaja. Dapat disimpulkan bahwa tenaga kesehatan, keluarga dan tingkat pengetahuan berperan dalam kehamilan remaja. Tenaga kesehatan perlu memberikan penyuluhan mengenai risiko kehamilan remaja kepada remaja serta keluarga. Worth 10.3% of indirect maternal death is due to teenage pregnancy (< 20 years old). In Tanah Datar District, the increase of teenage pregnancy has occured in the last three years. This study aimed to determine health worker's role, family's support and teenagers' knowledge with teenage pregnancy in work area of Singgalang Primary Health Care, Tanah Datar District in 2014. This study was conducted on May – June 2014 using cross-sectional design. Population was 215 married teenage girls < 20 years old. A total of sample was 68 selected proportionally in eight villages. Data were collected through interview using questionnaire. Then bivariate analysis was conducted using chi-square test and multivariate analysis using multiple logistic regression test. Results of study found 55.9% of respondents were pregnant in teen age. Respondents worth 52.9% got less health worker’s role, 66.2% got less family’s support and 58.8% had low level of knowledge. There was a relation found between health worker’s role (p value = 0.032), family’s support (p value = 0.025) and knowledge level (p value = 0.002) with teenage pregnancy. In conclusion, health workers, family and knowledge level play a role in teenage pregnancy. Health workers need to provide counseling concerning teenage pregnancy risks for both teenagers and families.
Pengaruh Musik Keroncong Selama Pelaksanaan Kangaroo Mother Care Terhadap Respons Fisiologis Dan Lama Rawat Bayi Dengan Berat Badan Lahir Rendah,
2015
Politeknik Kesehatan Kementerian Kesehatan Yogyakarta, Yogyakarta
Pengaruh Musik Keroncong Selama Pelaksanaan Kangaroo Mother Care Terhadap Respons Fisiologis Dan Lama Rawat Bayi Dengan Berat Badan Lahir Rendah, Anita Rahmawati, Endah Marianingsih Theresia, Yuliasti Eka Purnamaningrum
Kesmas
Kangaroo mother care (KMC) merupakan metode merawat bayi berat badan lahir rendah (BBLR). Beberapa intervensi perawatan di neonatal intensive care unit seperti pijat bayi, KMC, dan mendengarkan musik bermanfaat untuk pertumbuhan bayi berupa respons fisiologis BBLR dan mengurangi lama rawat. Penelitian ini bertujuan untuk mengetahui manfaat musik keroncong terhadap respons BBLR selama KMC dan lama rawat. Rancangan penelitian adalah quasi eksperimental dengan pretest dan posttest dengan desain grup kontrol. Pada Juli - September 2014 populasi penelitian adalah ibu dan bayi BBLR yang melaksanakan KMC. Pengambilan sampel dengan purposive sampling sebanyak 60 bayi. Kriteria inklusi bayi BBLR yang ditetapkan adalah berat …
A Localized Approach To The Origins Of Pottery In Upper Mesopotamia,
2015
University of Toronto
A Localized Approach To The Origins Of Pottery In Upper Mesopotamia, Elizabeth Gibbon
Laurier Undergraduate Journal of the Arts
No abstract provided.
Monitoring For Adverse Events Post Marketing Approval Of Drugs,
2015
Georgia Southern University
Monitoring For Adverse Events Post Marketing Approval Of Drugs, Karl E. Peace, Macaulay Okwuokenye
Biostatistics: Faculty Publications
This brief communication provides information to those developing monitoring plans for serious adverse events (SAE’s) following regulatory approval of a new drug. In addition, we (1) illustrate how many patients would need to be treated in order to have high confidence of seeing at least 1 pre-specified SAE, (2) show that absence of proof of a SAE is not proof of absence of that SAE, and (3) identify statistical methodology that could be used for formal statistical monitoring of SAE’s.
Meta-Analysis Of Genome-Wide Association Studies With Correlated Individuals: Application To The Hispanic Community Health Study/Study Of Latinos (Hchs/Sol),
2015
University of Washington
Meta-Analysis Of Genome-Wide Association Studies With Correlated Individuals: Application To The Hispanic Community Health Study/Study Of Latinos (Hchs/Sol), Tamar Sofer, John R. Shaffer, Misa Graff, Qibin Qi, Adrienne M. Stilp, Stephanie M. Gogarten, Kari E. North, Carmen R. Isasi, Cathy C. Laurie, Adam A. Szpiro
UW Biostatistics Working Paper Series
Investigators often meta-analyze multiple genome-wide association studies (GWASs) to increase the power to detect associations of single nucleotide polymorphisms (SNPs) with a trait. Meta-analysis is also performed within a single cohort that is stratified by, e.g., sex or ancestry group. Having correlated individuals among the strata may complicate meta-analyses, limit power, and inflate Type 1 error. For example, in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), sources of correlation include genetic relatedness, shared household, and shared community. We propose a novel mixed-effect model for meta-analysis, “MetaCor", which accounts for correlation between stratum-specific effect estimates. Simulations show that MetaCor controls …
Bayes Multiple Binary Classifier - How To Make Decisions Like A Bayesian,
2015
Florida International University
Bayes Multiple Binary Classifier - How To Make Decisions Like A Bayesian, Wensong Wu
Mathematics Colloquium Series
This presentation will start by a general introduction of Bayesian statistics, which has become popular in the era of big data. Then we consider a two-class classification problem, where the goal is to predict the class membership of M units based on the values of high-dimensional categorical predictor variables as well as both the values of predictor variables and the class membership of other N independent units. We focus on applying generalized linear regression models with Boolean expressions of categorical predictors. We consider a Bayesian and decision-theoretic framework, and develop a general form of Bayes multiple binary classification functions with …
Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology,
2015
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health
Nested Partially-Latent, Class Models For Dependent Binary Data, Estimating Disease Etiology, Zhenke Wu, Maria Deloria-Knoll, Scott L. Zeger
Johns Hopkins University, Dept. of Biostatistics Working Papers
The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unavailable. The paper describes a latent variable model designed to infer from case-control data the etiology distribution for the population of cases, and for an individual case given his or her measurements. We assume each observation is drawn from a mixture model for which each component represents one cause or disease class. The model addresses a major limitation of the traditional latent class approach by taking account of residual dependence among multivariate binary outcome …
Analysis Of Rheumatoid Arthritis Data Using Logistic Regression And Penalized Approach,
2015
University of South Florida
Analysis Of Rheumatoid Arthritis Data Using Logistic Regression And Penalized Approach, Wei Chen
USF Tampa Graduate Theses and Dissertations
In this paper, a rheumatoid arthritis (RA) medicine clinical dataset with an ordinal response is selected to study this new medicine. In the dataset, there are four features, sex, age,treatment, and preliminary. Sex is a binary categorical variable with 1 indicates male, and 0 indicates female. Age is the numerical age of the patients. And treatment is a binary categorical variable with 1 indicates has RA, and 0 indicates does not have RA. And preliminary is a five class categorical variable indicates the patient’s RA severity status before taking the medication. The response Y is 5 class ordinal variable shows …
Ensemble Learning Method On Machine Maintenance Data,
2015
University of South Florida
Ensemble Learning Method On Machine Maintenance Data, Xiaochuang Zhao
USF Tampa Graduate Theses and Dissertations
In the industry, a lot of companies are facing the explosion of big data. With this much information stored, companies want to make sense of the data and use it to help them for better decision making, especially for future prediction. A lot of money can be saved and huge revenue can be generated with the power of big data. When building statistical learning models for prediction, companies in the industry are aiming to build models with efficiency and high accuracy. After the learning models have been developed for production, new data will be generated. With the updated data, the …
Structural Properties Of Transmuted Weibull Distribution,
2015
University of Kashmir, Srinagar, India
Structural Properties Of Transmuted Weibull Distribution, Kaisar Ahmad, S. P. Ahmad, A. Ahmed
Journal of Modern Applied Statistical Methods
The transmuted Weibull distribution, and a related special case, is introduced. Estimates of parameters are obtained by using a new method of moments.
New Entropy Estimators With Smaller Root Mean Squared Error,
2015
Al al-Bayt University, Mafraq, Jordan
New Entropy Estimators With Smaller Root Mean Squared Error, Amer Ibrahim Al-Omari
Journal of Modern Applied Statistical Methods
New estimators of entropy of continuous random variable are suggested. The proposed estimators are investigated under simple random sampling (SRS), ranked set sampling (RSS), and double ranked set sampling (DRSS) methods. The estimators are compared with Vasicek (1976) and Al-Omari (2014) entropy estimators theoretically and by simulation in terms of the root mean squared error (RMSE) and bias values. The results indicate that the suggested estimators have less RMSE and bias values than their competing estimators introduced by Vasicek (1976) and Al-Omari (2014).
An Empirical Study On Different Ranking Methods For Effective Data Classification,
2015
K.L.N. College of Engineering, Madurai, India
An Empirical Study On Different Ranking Methods For Effective Data Classification, Ilangovan Sangaiah, A. Vincent Antony Kumar, Appavu Balamurugan
Journal of Modern Applied Statistical Methods
Ranking is the attribute selection technique used in the pre-processing phase to emphasize the most relevant attributes which allow models of classification simpler and easy to understand. It is a very important and a central task for information retrieval, such as web search engines, recommendation systems, and advertisement systems. A comparison between eight ranking methods was conducted. Ten different learning algorithms (NaiveBayes, J48, SMO, JRIP, Decision table, RandomForest, Multilayerperceptron, Kstar) were used to test the accuracy. The ranking methods with different supervised learning algorithms give different results for balanced accuracy. It was shown the selection of ranking methods could be …
Caution For Software Use Of New Statistical Methods (R),
2015
Dallas Independent School District, Dallas, TX
Caution For Software Use Of New Statistical Methods (R), Akiva J. Lorenz, Barry S. Markman, Shlomo Sawilowsky
Journal of Modern Applied Statistical Methods
Open source programming languages such as R allow statisticians to develop and rapidly disseminate advanced procedures, but sometimes at the expense of a proper vetting process. A new example is the least trimmed squares regression available in R’s lqs() in the MASS library. It produces pretty regression lines, particularly in the presence of outliers. However, this procedure lacks a defined standard error, and thus it should be avoided.
Inferences About The Skipped Correlation Coefficient: Dealing With Heteroscedasticity And Non-Normality,
2015
University of Southern California
Inferences About The Skipped Correlation Coefficient: Dealing With Heteroscedasticity And Non-Normality, Rand Wilcox
Journal of Modern Applied Statistical Methods
A common goal is testing the hypothesis that Pearson’s correlation is zero and typically this is done based on Student’s T test. There are, however, several well-known concerns. First, Student’s T is sensitive to heteroscedasticity. That is, when it rejects, it is reasonable to conclude that there is dependence, but in terms of making a decision about the strength of the association, it is unsatisfactory. Second, Pearson’s correlation is not robust: it can poorly reflect the strength of the association. Even a single outlier can have a tremendous impact on the usual estimate of Pearson’s correlation, which can result in …
Front Matter,
2015
Wayne State University
Jmasm34: Two Group Program For Cohen's D, Hedges’ G, Η2, Radj2, Ω2, Ɛ2, Confidence Intervals, And Power,
2015
Northern Illinois University
Jmasm34: Two Group Program For Cohen's D, Hedges’ G, Η2, Radj2, Ω2, Ɛ2, Confidence Intervals, And Power, David A. Walker
Journal of Modern Applied Statistical Methods
The purpose of this research is to provide an application for users interested in a SPSS syntax program to determine an array of commonly-employed effect sizes and confidence intervals not readily available in SPSS functionality, such as the standardized mean difference and r-related squared indices, for a between-group design.
Monte Carlo Comparison Of The Parameter Estimation Methods For The Two-Parameter Gumbel Distribution,
2015
Sinop University
Monte Carlo Comparison Of The Parameter Estimation Methods For The Two-Parameter Gumbel Distribution, Demet Aydin, Birdal Şenoğlu
Journal of Modern Applied Statistical Methods
The performances of the seven different parameter estimation methods for the Gumbel distribution are compared with numerical simulations. Estimation methods used in this study are the method of moments (ME), the method of maximum likelihood (ML), the method of modified maximum likelihood (MML), the method of least squares (LS), the method of weighted least squares (WLS), the method of percentile (PE) and the method of probability weighted moments (PWM). Performance of the estimators is compared with respect to their biases, MSE and deficiency (Def) values via Monte-Carlo simulation. A Monte Carlo Simulation study showed that the method of PWM was …
Contrails: Causal Inference Using Propensity Scores,
2015
twobluecats.com
Contrails: Causal Inference Using Propensity Scores, Dean S. Barron
Journal of Modern Applied Statistical Methods
Contrails are clouds caused by airplane exhausts, which geologists contend decrease daily temperature ranges on Earth. Following the 2001 World Trade Center attack, cancelled domestic flights triggered the first absence of contrails in decades. Resultant exceptional data capacitated causal inference analysis by propensity score matching. Estimated contrail effect was 6.8981°F.
Two Stage Robust Ridge Method In A Linear Regression Model,
2015
Ladoke Akintola University of Technology
Two Stage Robust Ridge Method In A Linear Regression Model, Adewale Folaranmi Lukman, Oyedeji Isola Osowole, Kayode Ayinde
Journal of Modern Applied Statistical Methods
Two Stage Robust Ridge Estimators based on robust estimators M, MM, S, LTS are examined in the presence of autocorrelation, multicollinearity and outliers as alternative to Ordinary Least Square Estimator (OLS). The estimator based on S estimator performs better. Mean square error was used as a criterion for examining the performances of these estimators.
