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RELEVANSI PENDIDIKAN HUKUM YANG SESUAI DENGAN PERKEMBANGAN MASYARAKAT
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| Pengarang | : | Muladi |
| Nama Majalah/Jurnal | : | Pranata |
| Volume / Edisi | : | I-2, DESEMBER (No. 0) |
| Halaman | : | 11-20 |
| Abstrak | : | - |
Distribution-Free Detection of Structured Anomalies: Permutation and Rank-Based Scans
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 113 (No. 522) |
| Halaman | : | 789-801 |
| Abstrak | : | The scan statistic is by far the most popular method for anomaly detection, being popular in syndromic surveillance, signal and image processing, and target detection based on sensor networks, among other applications. The use of the scan statistics in such settings yields a hypothesis testing procedure, where the null hypothesis corresponds to the absence of anomalous behavior. If the null distribution is known, then calibration of a scan-based test is relatively easy, as it can be done by Monte Carlo simulation. When the null distribution is unknown, it is less straightforward. We investigate two procedures. The first one is a calibration by permutation and the other is a rank-based scan test, which is distribution-free and less sensitive to outliers. Furthermore, the rank scan test requires only a one-time calibration for a given data size making it computationally much more appealing. In both cases, we quantify the performance loss with respect to an oracle scan test that knows the null distribution. We show that using one of these calibration procedures results in only a very small loss of power in the context of a natural exponential family. This includes the classical normal location model, popular in signal processing, and the Poisson model, popular in syndromic surveillance. We perform numerical experiments on simulated data further supporting our theory and also on a real dataset from genomics. Supplementary materials for this article are available online. |
SISTEM PENDIDIKAN NASIONAL DAN PENDIDIKAN SERTA PENGAJARAN DI PERGURUAN TINGGI
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Pranata |
| Volume / Edisi | : | I-2, DESEMBER (No. 0) |
| Halaman | : | 1-10 |
| Abstrak | : | - |
Parametric-Rate Inference for One-Sided Differentiable Parameters
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 113 (No. 522) |
| Halaman | : | 780-788 |
| Abstrak | : | Suppose one has a collection of parameters indexed by a (possibly infinite dimensional) set. Given data generated from some distribution, the objective is to estimate the maximal parameter in this collection evaluated at the distribution that generated the data. This estimation problem is typically nonregular when the maximizing parameter is nonunique, and as a result standard asymptotic techniques generally fail in this case. We present a technique for developing parametric-rate confidence intervals for the quantity of interest in these nonregular settings. We show that our estimator is asymptotically efficient when the maximizing parameter is unique so that regular estimation is possible. We apply our technique to a recent example from the literature in which one wishes to report the maximal absolute correlation between a prespecified outcome and one of p predictors. The simplicity of our technique enables an analysis of the previously open case where p grows with sample size. Specifically, we only require that log p grows slower than √????, where n is the sample size. We show that, unlike earlier approaches, our method scales to massive datasets: the point estimate and confidence intervals can be constructed in O(np) time. Supplementary materials for this article are available online. |
On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
| Pengarang | : | Sebastian Calonico |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 113 (No. 522) |
| Halaman | : | 767-779 |
| Abstrak | : | Nonparametric methods play a central role in modern empirical work. While they provide inference procedures that are more robust to parametric misspecification bias, they may be quite sensitive to tuning parameter choices. We study the effects of bias correction on confidence interval coverage in the context of kernel density and local polynomial regression estimation, and prove that bias correction can be preferred to undersmoothing for minimizing coverage error and increasing robustness to tuning parameter choice. This is achieved using a novel, yet simple, Studentization, which leads to a new way of constructing kernel-based bias-corrected confidence intervals. In addition, for practical cases, we derive coverage error optimal bandwidths and discuss easy-to-implement bandwidth selectors. For interior points, we show that the mean-squared error (MSE)-optimal bandwidth for the original point estimator (before bias correction) delivers the fastest coverage error decay rate after bias correction when second-order (equivalent) kernels are employed, but is otherwise suboptimal because it is too “large.” Finally, for odd-degree local polynomial regression, we show that, as with point estimation, coverage error adapts to boundary points automatically when appropriate Studentization is used; however, the MSE-optimal bandwidth for the original point estimator is suboptimal. All the results are established using valid Edgeworth expansions and illustrated with simulated data. Our findings have important consequences for empirical work as they indicate that bias-corrected confidence intervals, coupled with appropriate standard errors, have smaller coverage error and are less sensitive to tuning parameter choices in practically relevant cases where additional smoothness is available. Supplementary materials for this article are available online. |
Hidden Population Size Estimation From Respondent-Driven Sampling: A Network Approach
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of the American Statistical Association |
| Volume / Edisi | : | 113 (No. 522) |
| Halaman | : | 755-766 |
| Abstrak | : | Estimating the size of stigmatized, hidden, or hard-to-reach populations is a major problem in epidemiology, demography, and public health research. Capture–recapture and multiplier methods are standard tools for inference of hidden population sizes, but they require random sampling of target population members, which is rarely possible. Respondent-driven sampling (RDS) is a survey method for hidden populations that relies on social link tracing. The RDS recruitment process is designed to spread through the social network connecting members of the target population. In this article, we show how to use network data revealed by RDS to estimate hidden population size. The key insight is that the recruitment chain, timing of recruitments, and network degrees of recruited subjects provide information about the number of individuals belonging to the target population who are not yet in the sample. We use a computationally efficient Bayesian method to integrate over the missing edges in the subgraph of recruited individuals. We validate the method using simulated data and apply the technique to estimate the number of people who inject drugs in St. Petersburg, Russia. Supplementary materials for this article are available online. |
A Long-Term Investigation of the Science Teaching Efficacy Beliefs of Multiple Cohorts of Preservice Elementary Teachers
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of Science Teacher Education |
| Volume / Edisi | : | 30 (No. 7-8) |
| Halaman | : | 923–945 |
| Abstrak | : | If the declines in interest and performance within school science are to be reversed, it is imperative that competent and confident tea chers deliver quality science experiences. This paper reports on the long-term implementation of two complementary, student-centered tertiary science methods courses that integrated instruction in con tent with teaching methods within a preservice elementary teaching degree. The Science Teaching Efficacy Belief Instrument B was employed to collect data from multiple cohorts (2007–2014). Multiple iterations of the quasi–experimental design were employed. Complete data supplied by 234 preservice teachers were analyzed using MANOVA with repeated measures on the occasion of testing. Results indicate that personal and outcome efficacy beliefs grew significantly with moderate to large effect sizes, in ways that are atypical within the literature. Broader implications are discussed. |
The Role of Teacher Framing in Producing Coherent NGSS-Aligned Teaching
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of Science Teacher Education |
| Volume / Edisi | : | 30 (No. 7-8) |
| Halaman | : | 906–922 |
| Abstrak | : | Wereport on one teachers’ efforts to re-design an entire instructional unit as a coherent storyline about forces and motion as a part of a multiyear professional development (PD) project around the NGSS. Designing coherent storylines demands that teachers create opportu nities for students to meaningfully engage in science practices in order to develop their knowledge over time. We found that appropriately framing the unit, lesson, and/or activity supported students take on roles as epistemic agents and sensemakers, whereas unclear framing led to more traditional roles for students that resembled didactic science teaching. This suggests that a primary issue for PD is to help teachers look at and plan how they intend to frame lessons/activities as a way for them to promote coherence and epistemic agency. |
Validating A Model for Assessing Science Teacher’s Adaptive Expertise with Computer-Supported Complex Systems Curricula and Its Relationship to Student Learning Outcomes
| Pengarang | : | Yoon, Susan A.,Evans, Chad,Miller, Katherine,Anderson, Emma,Koehler, Jessica |
| Nama Majalah/Jurnal | : | Journal of Science Teacher Education |
| Volume / Edisi | : | 30 (No. 7-8) |
| Halaman | : | 890–905 |
| Abstrak | : | The success of the Next Generation Science Standards (NGSS) and similar reforms is contingent upon the quality of teaching, yet the shifts in teaching practice required are substantial. In this study, we propose and validate a model of adaptive expertise needed for teachers to success fully deliver NGSS-informed computer-supported complex systems cur ricula in high school science classrooms. The model is comprised of three research-based qualities that we hypothesize teachers need to demonstrate: flexibility, deeper-level understanding,anddeliberate prac tice, in adapting interventions to their particular teaching contexts. We apply the model to (a) test whether there is variation between teachers in these qualities and (b) confirm that there exists a relationship betweenthese qualities and student-learning outcomes. Teacher enact ments and interview responses reveal significant variation and are also predictive of students’ growth in complex systems understanding. The modelhasimportantimplications for howtosupport teachers inadopt ing new science education reforms that are specific to computer supported complex systems curricula and instruction. |
The Impact of a Summer Camp-Based Science Methods Course on Preservice Teachers’ Self-Efficacy in Teaching Science as Inquiry
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Journal of Science Teacher Education |
| Volume / Edisi | : | 30 (No. 7-8) |
| Halaman | : | 872–889 |
| Abstrak | : | The purpose of this research is to examine the effect of a summer camp-based science methods course on elementary pre-service tea chers’ self-efficacy in teaching science as inquiry. The science camp was offered to K-6 students as part of the 4-week, 3-credit science teaching methods course over the summer. The preservice teachers were asked to teach camp children for two weeks for their practicum requirement. This study utilized a mixed-methods design using both qualitative and quantitative data collected with 55 participants over four years. The TSI (Teaching Science as Inquiry) was administered at the beginning and end of the course to estimate participants’ self efficacy. We only measured PSTEB (Personal Science Teaching Efficacy Belief) using 34 items out of the TSI to reduce test fatigue. We also conducted semi-structured interviews at the end of the course to investigate sources for their self-efficacy. The paired samples t-test of the pre- and post-course survey indicates that preservice teachers’ self-efficacy in teaching science as inquiry increased significantly as a result of participating in the course (p < .001). Analysis of the interview data revealed eight main sources of self-efficacy and each one’s relative significance compared to other sources. The findings of this study imply that the camp-based course increased pre-service teachers’ self-efficacy by providing not only various mastery experi ences, but also unique experiences that afforded reflection and men toring, and drew camp participants’ positive reactions. This study highlights the potential of informal science education settings as f ield experience sites especially for elementary science methods courses |