Background: Most investigators use ordinary least squares (OLS) methods to model low birth weight. When the data are non-normal or contain outliers, OLS become ineffective. However, the quantile method of forecasting low birth weight has not been fully evaluated, although it has good potential for overcoming problems associated with linear regression. Methods: The present study reports our comparison between the OLS and quantile regression methods for modeling low birth weight when the data are right skewed and outliers are presented. Additionally, we evaluated the performance of the associated algorithm in recovering the true parameter using the bootstrap method. Results: Our study found that a mother's education level, the number of maternal parities, and the last birth interval significantly impacted low birth weight at any selected low quantile. Based on the bootstrap simulation study, the proposed model was considered to be acceptable since both methods generated nearly identical estimates of the parameter model. An accuracy test proved that the quantile method was an unbiased estimator. Conclusions: The present study found that low birth weight is significantly affected by the mother's educational level, the number of maternal parities, and the last birth interval.

This study aims to implement Bayesian quantile regression method in constructing the model of Low Birth Weight. The data of Low Birth Weight is violated of nonnormal assumption for error terms. This study considers quantile regression approach and use Gibbs sampling algorithm from Bayesian method for fitting the quantile regression model. This study explores the performance of the asymmetric Laplace distribution for working likelihood in posterior estimation process. This study also compare the result of variable selection in quantile regression and Bayesian quantile regression for Low Birth Weight model. This study. proved that Bayesan quantile method produced better model than just quantile approach. Bayesian quantile method proved that it can handle the nonnormal problem although using moderate size of data.

The main objective of this present study is to demonstrate the application of reliability tests and their consistency on any constructs of patient loyalty model using SEM appproach. There are three reliability tests implemented here, i.e Coefficient of Reliability (CR), Coefficient of Reliability Composite Score McDonald's ω, and Coefficient of Reliability Construct Weighted. After implementing those three reliability tests to the data, this empirical study found that all reliability tests result almost the same values. The consistency of all three reliability test are then checked by simulation study. The simulation study prove that all reliability tests are consistence as well, the values of reliability index are almost the same for various size of samples. It is concluded here that any constructs in proposed model of patient loyalty is reliable and the coresponding proposed model could be accepted.

Pemilihan umum di Indonesia yang dilaksanakan sejak tahun 1955 berjalan tanpa memiliki alat ukur dan indikator kualitas Pemilu yang jelas. Peningkatkan kualitas pemilu merupakan salah satu kunci mewujudkan demokrasi berkualitas. Indikator standar dan penilaian kualitas pemilu pada penelitian terdahulu tidak mampu merepresentasikan prinsip nilai demokrasi Pancasila, nilai budaya politik lokal, dan kondisi masyarakat Indonesia yang heterogen, sehingga perlu adanya kajian khusus yang meperbaiki standar kualitas Pemilu sesuai dengan keadaan di Indonesia. Tujuan penelitian ini adalah untuk mengembangkan indikator dan instrumen penilaian kualitas pemilu nasional di Indonesia. Metode penelitian yang digunakan adalah studi kepustakaan didukung oleh hasil penelitian yang relevan. Indikator penilaian kualitas pemilu dibangun melalui seluruh aspek proses tata kelola pemilu pra, masa dan pasca pemilu. Keseluruhan aspek tersebut memenuhi prinsip kesetaraan, kebebasan, keadilan, transparansi, profesionalitas, keamanan, integritas dan penyesuaian budaya politik lokal. Penilaian kualitas pemilu dapat dilakukan melalui metode jejak pendapat dan diukur dengan skala pengukuran ordinal. Standarisasi Indeks kualitas pemilu nasional yang dibentuk dan dikembangkan sesuai dengan perkembangan zaman, menjamin keakuratan pengukuran kualitas pemilu, sehingga kualitas pemilu dapat diperbaiki secara berkelanjutan dan konsisten.

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