1,720,959 research outputs found
Model Persamaan Simultan untuk Pendugaan Area Kecil.
No full textPendugaan area kecil (SAE) menjadi metode statistik yang penting sehubungan
dengan meningkatnya permintaan atas penyediaan statistik yang
terpercaya dari suatu survei untuk area kecil dimana jumlah contohnya tidak
mencukupi. Penduga langsung untuk area kecil yang dihasilkan dari suatu
survei menjadi tidak dapat dipercaya karena menghasilkan galat baku yang
besar. Metode SAE dapat meningkatkan efektivitas contoh dengan memanfaatkan
kekuatan area yang bertetanggaan dan informasi dari peubah
penyerta yang mempunyai hubungan kuat dengan peubah yang diamati.
Dalam aplikasinya, metode SAE diterapkan pertama kalinya oleh Fay
dan Herriot (1979) menggunakan model campuran linier dengan pengaruh
acak area untuk menduga pendapatan perkapita (PCI) pada area kecil di
Amerika Serikat. Kemudian Prasad dan Rao (1990); Lahiri dan Rao (1995);
Datta dan Lahiri (2000) dan Das dkk (2004) mengembangkan beberapa
metode untuk mengukur keragaman dugaan rata-rata pada level area. Pada
kasus peubah ganda, Fay (1987); Datta dkk (1991, 1996) mengembangkan
model Fay-Herriot multivariat (MFH) untuk SAE. Kemudian Benavent dan
Morales (2016) mengembangkan model MFH dengan mempertimbangkan
struktur matriks peragam yang berbeda-beda pada pengaruh acak area.
Model MFH memanfaatkan beberapa keuntungan penggunaan korelasi
antara beberapa peubah yang diamati. Namun, beberapa peubah amatan
yang dihasilkan oleh beberapa survei tersebut berkemungkinan tidak hanya
saling berkorelasi, akan tetapi antar beberapa peubah amatan tersebut juga
mempunyai hubungan yang saling mempengaruhi. Dalam kasus ini, penggunaan
model MFH menjadi tidak tepat karena model MFH tidak dapat
menghitung pengaruh hubungan antara peubah amatan. Oleh karena itu,
penggunaan model persamaan simultan (SEM) untuk pendugaan area kecil
menjadi sesuatu yang diperlukan.
Sainath (2014) memperkenalkan penggunaan model campuran persamaan
struktural (SEMM) dengan menerapkannya pada data simulasi
untuk SAE. Untuk memperoleh dugaan parameter SEMM, Sainath (2014)
menggunakan metode peubah instrumen kemungkinan maksimum terkendala
(IV-REML) yang menghasilkan kinerja lebih baik daripada metode
komponen galat kuadrat terkecil tiga tahap (EC3SLS) yang dikembangkan
oleh Baltagi (1981). Akan tetapi, Sainath (2014) belum secara jelas merumuskan
penduga linier tak bias terbaik (BLUP) dan penduga ragam dari
penduga BLUP sebagai konsep dasar dalam SAE. Oleh karena itu, menjadi
penting untuk mengembangkan penduga BLUP dan penduga ragamnya
berbasis SEMM.
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Disertasi ini mengembangkan model persamaan simultan Fay-Herriot
(SEFH) untuk pendugaan area kecil. Model SEFH ini merupakan bentuk
pengembangan dari model MFH dengan melibatkan peubah endogen sebagai
peubah penjelas dalam model. Penduga linier tak bias terbaik (BLUP)
dan penduga kuadrat tengah galat (MSE) dari BLUP empirik dikembangkan
dalam disertasi ini. Algoritma baru untuk menduga parameter model SEFH,
yaitu algoritma kuadrat terkecil tiga tahap kemungkinan maksimum terkendala
(3SLS-REML) juga dikembangkan dalam disertasi ini.
Beberapa kajian simulasi telah dilakukan dalam disertasi ini untuk menilai
kinerja model yang dikembangkan dalam hal bias dan efisiensi hasil
dugaan parameter. Kajian-kajian simulasi menunjukkan bahwa model yang
dikembangkan (model SEFH) dapat menghasilkan dugaan parameter yang
lebih efisien dibandingkan dengan hasil dugaan model MFH. Dapat ditunjukkan
juga dalam aplikasi data riil bahwa bahwa model yang dikembangkan
(model SEFH) menghasilkan dugaan parameter yang lebih efisien
dari pada model MFH. Lebih lanjut, hasil dugaan akar kuadrat tengah galat
(RMSE) dari EBLUP berbasis model SEFH bernilai lebih kecil dibandingkan
dugaan RMSE dari pendugaan langsung
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
msae: An R Package of Multivariate Fay-Herriot Models for Small Area Estimation
Full text linkThe paper introduces an R Package of multivariate Fay-Herriot models for small area estimation named msae. This package implements four types of Fay-Herriot models, including univariate Fay-Herriot model (model 0), multivariate Fay-Herriot model (model 1), autoregressive multivariate Fay-Herriot model (model 2), and heteroskedastic autoregressive multivariate Fay-Herriot model (model 3). It also contains some datasets generated based on multivariate Fay-Herriot models. We describe and implement functions through various practical examples. Multivariate Fay-Herriot models produce a more efficient parameter estimation than direct estimation and univariate model
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Application of Small Area Estimation for Global Hunger Index at Regency/Municipality Level in Papua Island
Full text linkReducing hunger is one of the primary targets of the Sustainable Development Goals (SDGs), particularly Goal 2: Zero Hunger. The Global Hunger Index (GHI) is a key indicator used to measure hunger, comprising four components: the prevalence of undernourishment (PoU), child mortality rate, child stunting, and wasting. While PoU and child mortality data are available at the district/city level across Indonesia, limited data on stunting and wasting in several makes it difficult to calculate the GHI at the local level. Data limitations hinder the formulation of locally targeted policies. This study aims GHI in Papua Province using the Small Area Estimation (SAE) approach. Data sources include the 2023 Indonesia Health Survey and Podes 2021. , while wasting is estimated using the Hierarchical Bayes Beta approach. that SAE improves estimation precision compared to direct estimation, as reflec by . Estimates reveal GHI may vary in category between serious to extremely alarming, with Jayapura City having the lowest and Dogiyai as the highest GHI in Papua.
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