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Instrumen Hukum Penodaan Agama dan Peraturan Menteri: Sebuah Pencegahan atau Sumber Konflik?
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| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis CSIS |
| Volume / Edisi | : | 46 (No. 1) |
| Halaman | : | 50-70 |
| Abstrak | : | Permasalahan relasi negara dan agama menjadi isu yang semakin relevan dalam kurun waktu beberapa tahun terakhir. Khususnya, seputar Pilkada DKI Jakarta tahun 2017, isu penistaan agama mencuat dalam perhatian nasional. Penistaan agama dan Undang-Undang PNPS 1965 bukan merupakan suatu hal baru. Pemerintah dan beberapa organisasi masyarakat telah menekankan bahwa perlunya Undang-Undang tersebut untuk mencegah konflik antar-umat beragama ketika UU tersebut di judicial review tahun 2009-2010. Namun demikian, sampai saat ini perbedaan pendapat anatara aktifis kebebasan beragama dan pihak pemerintah, serta kelompok agama tidak terjembatani oleh riset yang berbasis data. Pertanyaan utama artikel ini adalah: "Apakah regulasi yang ada pada PNPS 1965 mencegah konflik atau justru menyebabkan konflik?" Sementara, pada temuan penelitian ini adalah bahwa PNPS 1965 justru menjadi kerangka bukum yang menjadi ruang konflik dalam masyarakat. Akan tetapi pada penelitian ini tidak dinyatakan sudah sahih temuannya secara komprehensif, masih banyak aspek lain yang perlu diteliti lebih lanjut. Hanya saja, temuan awal yang ada sudah cukup menunjukkan permasalahan yang disebabkan oleh UU PNPS 1965. |
Tinjauan Perkembangan Regional dan Global: Politik OBOR dan Kegelisahan di Asia Tenggara
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis CSIS |
| Volume / Edisi | : | 46 (No. 1) |
| Halaman | : | 42-49 |
| Abstrak | : | - |
Tinjauan Perkembangan Ekonomi: Menyoal Pertumbuhan Yang Lebih Inklusif di Tahun 2017
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis CSIS |
| Volume / Edisi | : | 46 (No. 1) |
| Halaman | : | 23-41 |
| Abstrak | : | - |
Tinjauan Perkembangan Politik: Tahun Politik 2017: Konsolidasi Politik dan Tantangan Demokrasi Lokal
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis CSIS |
| Volume / Edisi | : | 46 (No. 1) |
| Halaman | : | 7-22 |
| Abstrak | : | - |
A Comparative Review of Nonparametric Statistics Textbooks
| Pengarang | : | Alice Richardson |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 73 (No. 4) |
| Halaman | : | 360-366 |
| Abstrak | : | In this article I will review six textbooks commonly set in University undergraduate nonparametric statistics courses. The books will be evaluated in terms of how key statistical concepts are presented; use of software; exercises; and location on a theory-applications axis and an algorithms-principles axis. The placement of books on these axes provides a novel guide for instructors looking for the book that best fits their approach to teaching nonparametric statistics. |
Power and Sample Size for Fixed-Effects Inference in Reversible Linear Mixed Models
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 73 (No. 4) |
| Halaman | : | 350-359 |
| Abstrak | : | Despite the popularity of the general linear mixed model for data analysis, power and sample size methods and software are not generally available for commonly used test statistics and reference distributions. Statisticians resort to simulations with homegrown and uncertified programs or rough approximations which are misaligned with the data analysis. For a wide range of designs with longitudinal and clustering features, we provide accurate power and sample size approximations for inference about fixed effects in the linear models we call reversible. We show that under widely applicable conditions, the general linear mixed-model Wald test has noncentral distributions equivalent to well-studied multivariate tests. In turn, exact and approximate power and sample size results for the multivariate Hotelling–Lawley test provide exact and approximate power and sample size results for the mixed-model Wald test. The calculations are easily computed with a free, open-source product that requires only a web browser to use. Commercial software can be used for a smaller range of reversible models. Simple approximations allow accounting for modest amounts of missing data. A real-world example illustrates the methods. Sample size results are presented for a multicenter study on pregnancy. The proposed study, an extension of a funded project, has clustering within clinic. Exchangeability among the participants allows averaging across them to remove the clustering structure. The resulting simplified design is a single-level longitudinal study. Multivariate methods for power provide an approximate sample size. All proofs and inputs for the example are in the supplementary materials (available online). |
Bias Reduction in Logistic Regression with Missing Responses When the Missing Data Mechanism is Nonignorable
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 73 (No. 4) |
| Halaman | : | 340-349 |
| Abstrak | : | In logistic regression with nonignorable missing responses, Ibrahim and Lipsitz proposed a method for estimating regression parameters. It is known that the regression estimates obtained by using this method are biased when the sample size is small. Also, another complexity arises when the iterative estimation process encounters separation in estimating regression coefficients. In this article, we propose a method to improve the estimation of regression coefficients. In our likelihood-based method, we penalize the likelihood by multiplying it by a noninformative Jeffreys prior as a penalty term. The proposed method reduces bias and is able to handle the issue of separation. Simulation results show substantial bias reduction for the proposed method as compared to the existing method. Analyses using real world data also support the simulation findings. An R package called brlrmr is developed implementing the proposed method and the Ibrahim and Lipsitz method. |
A Bayes Factor for Replications of ANOVA Results
| Pengarang | : | |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 73 (No. 4) |
| Halaman | : | 327-339 |
| Abstrak | : | With an increasing number of replication studies performed in psychological science, the question of how to evaluate the outcome of a replication attempt deserves careful consideration. Bayesian approaches allow to incorporate uncertainty and prior information into the analysis of the replication attempt by their design. The Replication Bayes factor, introduced by Verhagen and Wagenmakers (Citation2014), provides quantitative, relative evidence in favor or against a successful replication. In previous work by Verhagen and Wagenmakers (Citation2014), it was limited to the case of t-tests. In this article, the Replication Bayes factor is extended to F-tests in multigroup, fixed-effect ANOVA designs. Simulations and examples are presented to facilitate the understanding and to demonstrate the usefulness of this approach. Finally, the Replication Bayes factor is compared to other Bayesian and frequentist approaches and discussed in the context of replication attempts. R code to calculate Replication Bayes factors and to reproduce the examples in the article is available at https://osf.io/jv39h/. |
A Five-Decision Testing Procedure to Infer the Value of a Unidimensional Parameter
| Pengarang | : | Aaron McDaid |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 73 (No. 4) |
| Halaman | : | 321-326 |
| Abstrak | : | A statistical test can be seen as a procedure to produce a decision based on observed data, where some decisions consist of rejecting a hypothesis (yielding a significant result) and some do not, and where one controls the probability to make a wrong rejection at some prespecified significance level. Whereas traditional hypothesis testing involves only two possible decisions (to reject or not a null hypothesis), Kaiser’s directional two-sided test as well as the more recently introduced testing procedure of Jones and Tukey, each equivalent to running two one-sided tests, involve three possible decisions to infer the value of a unidimensional parameter. The latter procedure assumes that a point null hypothesis is impossible (e.g., that two treatments cannot have exactly the same effect), allowing a gain of statistical power. There are, however, situations where a point hypothesis is indeed plausible, for example, when considering hypotheses derived from Einstein’s theories. In this article, we introduce a five-decision rule testing procedure, equivalent to running a traditional two-sided test in addition to two one-sided tests, which combines the advantages of the testing procedures of Kaiser (no assumption on a point hypothesis being impossible) and Jones and Tukey (higher power), allowing for a nonnegligible (typically 20%) reduction of the sample size needed to reach a given statistical power to get a significant result, compared to the traditional approach. |
Test for Trend With a Multinomial Outcome
| Pengarang | : | Aniko Szabo |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 73 (No. 4) |
| Halaman | : | 313-320 |
| Abstrak | : | There is no established procedure for testing for trend with nominal outcomes that would provide both a global hypothesis test and outcome-specific inference. We derive a simple formula for such a test using a weighted sum of Cochran–Armitage test statistics evaluating the trend in each outcome separately. The test is shown to be equivalent to the score test for multinomial logistic regression, however, the new formulation enables the derivation of a sample size formula and multiplicity-adjusted inference for individual outcomes. The proposed methods are implemented in the R package multiCA. |