scholarly journals What Countries Select More Experienced Leaders? The PolEx Measure of Political Experience

2021 ◽  
pp. 1-10
Author(s):  
Alexander Baturo ◽  
Johan A. Elkink
Keyword(s):  
Career Paths ◽  
Latent Variable ◽  
Empirical Studies ◽  
Future Research ◽  
Variable Model ◽  
Data Set ◽  
Political Experience ◽  
National Leaders ◽  
Regime Types ◽  
The Difference

Abstract How can one assess which countries select more experienced leaders for the highest office? There is wide variation in prior career paths of national leaders within, and even more so between, regime types. It is therefore challenging to obtain a truly comparative measure of political experience; empirical studies have to rely on proxies instead. This article proposes PolEx, a measure of political experience that abstracts away from the details of career paths and generalizes based on the duration, quality and breadth of an individual's experience in politics. The analysis draws on a novel data set of around 2,000 leaders from 1950 to 2017 and uses a Bayesian latent variable model to estimate PolEx. The article illustrates how the new measure can be used comparatively to assess whether democracies select more experienced leaders. The authors find that while on average they do, the difference with non-democracies has declined dramatically since the early 2000s. Future research may leverage PolEx to investigate the role of prior political experience in, for example, policy making and crisis management.

Information Matrices in Latent-Variable Models

1989 ◽  
Vol 14 (4) ◽  
pp. 335-350 ◽  
Author(s):  
Robert J. Mislevy ◽  
Kathleen M. Sheehan
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Information Matrix ◽  
Missing Information ◽  
Variable Model ◽  
Related Information ◽  
Expected Information ◽  
The Difference ◽  
Information Matrices ◽  
Practical Implications

The Fisher, or expected, information matrix for the parameters in a latent-variable model is bounded from above by the information that would be obtained if the values of the latent variables could also be observed. The difference between this upper bound and the information in the observed data is the “missing information.” This paper explicates the structure of the expected information matrix and related information matrices, and characterizes the degree to which missing information can be recovered by exploiting collateral variables for respondents. The results are illustrated in the context of item response theory models, and practical implications are discussed.

scholarly journals A Shift-Invariant Latent Variable Model for Automatic Music Transcription

2012 ◽  
Vol 36 (4) ◽  
pp. 81-94 ◽  
Author(s):  
Emmanouil Benetos ◽  
Simon Dixon
Keyword(s):  
Latent Variable ◽  
Markov Models ◽  
Variable Model ◽  
Data Set ◽  
Music Transcription ◽  
Transcription System ◽  
Automatic Music Transcription ◽  
Error Metrics ◽  
Frequency Modulations ◽  
Time Varying Pitch

In this work, a probabilistic model for multiple-instrument automatic music transcription is proposed. The model extends the shift-invariant probabilistic latent component analysis method, which is used for spectrogram factorization. Proposed extensions support the use of multiple spectral templates per pitch and per instrument source, as well as a time-varying pitch contribution for each source. Thus, this method can effectively be used for multiple-instrument automatic transcription. In addition, the shift-invariant aspect of the method can be exploited for detecting tuning changes and frequency modulations, as well as for visualizing pitch content. For note tracking and smoothing, pitch-wise hidden Markov models are used. For training, pitch templates from eight orchestral instruments were extracted, covering their complete note range. The transcription system was tested on multiple-instrument polyphonic recordings from the RWC database, a Disklavier data set, and the MIREX 2007 multi-F0 data set. Results demonstrate that the proposed method outperforms leading approaches from the transcription literature, using several error metrics.

Diagnostic image quality of hand-held and wall-mounted X-ray devices in bitewing radiography: a non-inferiority clinical trial

2021 ◽  
pp. 20200471
Author(s):  
Reinier Cornelis Hoogeveen ◽  
Siham Ouchene ◽  
WER Berkhout
Keyword(s):  
Clinical Trial ◽  
Image Quality ◽  
Future Research ◽  
Diagnostic Image Quality ◽  
Data Set ◽  
Diagnostic Image ◽  
X Ray ◽  
The Difference ◽  
Diagnostic Modalities

Objectives: The present clinical trial was intended to clarify whether subjective assessments of diagnostic X-ray image quality achieved via hand-held (HH) Nomad Pro 2 (KaVo Kerr, Brea, CA, USA) X-ray device is non-inferior that of the wall-mounted (WM) KaVo Focus (KaVo Dental, Bieberich, Germany). Methods: A prospective, cross-over, and in vivo non-inferiority clinical trial was conducted to compare these two diagnostic modalities. Based on sampling calculations, 205 patients were selected for study, generating 410 paired bitewing radiographs in randomized sequence. The films were assessed independently, engaging three observers blinded to modality for random, side-by-side-comparisons. Diagnostic image quality was rated as follows: no preference, HH preference, or WM preference. Observer judgements were combined accordingly to reach a majority. Results: Collective observer ratings indicated no preference for diagnostic image quality in 63.9% of cases, with WM preference at 16.6% and HH preference at 19.5%. The difference in HH and WM preferences (19.5%–16.6% = 2.9%) was within the expected 95% confidence interval. Majority agreement was reached in 82.7%. Conclusions: Subjectively assessed diagnostic image quality in bitewing radiographs acquired by HH and WM devices did not differ significantly. The hand-held device is thus non-inferior to the WM in this regard. Our data set of paired bitewing radiographs may subsequently aid in future research.

scholarly journals Evaluative application of UKCP09‐based downscaled future weather years to simulate overheating risk in typical English homes

2013 ◽  
Vol 31 (4) ◽  
pp. 231-252 ◽  
Author(s):  
Rajat Gupta ◽  
Matthew Gregg ◽  
Hu Du ◽  
Katie Williams
Keyword(s):  
Climate Change ◽  
Simulation Modelling ◽  
Simulation Software ◽  
Building Simulation ◽  
Future Research ◽  
Climate Projections ◽  
Data Sets ◽  
Data Set ◽  
Content Type ◽  
The Difference

PurposeTo critically compare three future weather year (FWY) downscaling approaches, based on the 2009 UK Climate Projections, used for climate change impact and adaptation analysis in building simulation software.Design/methodology/approachThe validity of these FWYs is assessed through dynamic building simulation modelling to project future overheating risk in typical English homes in 2050s and 2080s.FindingsThe modelling results show that the variation in overheating projections is far too significant to consider the tested FWY data sets equally suitable for the task.Research and practical implicationsIt is recommended that future research should consider harmonisation of the downscaling approaches so as to generate a unified data set of FWYs to be used for a given location and climate projection. If FWY are to be used in practice, live projects will need viable and reliable FWY on which to base their adaptation decisions. The difference between the data sets tested could potentially lead to different adaptation priorities specifically with regard to time series and adaptation phasing through the life of a building.Originality/valueThe paper investigates the different results derived from FWY application to building simulation. The outcome and implications are important considerations for research and practice involved in FWY data use in building simulation intended for climate change adaptation modelling.

A latent variable approach to measuring wartime sexual violence

2020 ◽  
Vol 57 (6) ◽  
pp. 728-739
Author(s):  
Jule Krüger ◽  
Ragnhild Nordås
Keyword(s):  
Sexual Violence ◽  
Latent Variable ◽  
Best Practice ◽  
Temporal Trends ◽  
Credible Interval ◽  
Future Research ◽  
Variable Model ◽  
Multiple Indicators ◽  
Variable Approach ◽  
Security Problem

Conflict-related sexual violence is an international security problem and is sometimes used as a weapon of war. It is also a complex and hard-to-observe phenomenon, constituting perhaps one of the most hidden forms of wartime violence. Latent variable models (LVM) offer a promising avenue to account for differences in observed measures. Three annual human rights sources report on the sexual violence practices of armed conflict actors around the world since 1989 and were coded into ordinal indicators of conflict-year prevalence. Because information diverges significantly across these measures, we currently have a poor scientific understanding with regard to trends and patterns of the problem. In this article, we use an LVM approach to leverage information across multiple indicators of wartime sexual violence to estimate its true extent, to express uncertainty in the form of a credible interval, and to account for temporal trends in the underlying data. We argue that a dynamic LVM parametrization constitutes the best fit in this context. It outperforms a static latent variable model, as well as analysis of observed indicators. Based on our findings, we argue that an LVM approach currently constitutes the best practice for this line of inquiry and conclude with suggestions for future research.

A Research on Gaussian Process Based Feature Extraction

2013 ◽  
Vol 300-301 ◽  
pp. 848-852
Author(s):  
Zong Hai Sun ◽  
Osman Osman
Keyword(s):  
Feature Extraction ◽  
Gaussian Process ◽  
Latent Variable ◽  
Original Data ◽  
Data Sets ◽  
Real World Data ◽  
Cancer Treatments ◽  
Variable Model ◽  
Data Set ◽  
Comparison Of The Results

Data sets of high–dimensional spaces are problematic when it comes to classification, compression, and visualization. The main issue is to find a reduced dimensionality representation that corresponds to the intrinsic dimensionality of the original data. In this paper we try to investigate a practical Bayesian method for feature extracting problem, in particular we will apply Gaussian Process Latent Variable Model (GPLVM) to a real world data set. Feature extraction experiments were performed on a cancer treatments’ components data set using GPLVM, then we used PCA on the same data set for comparison of the results.

scholarly journals The Effect of Stepfathers on Self-Perception and Familial Support

2019 ◽  
Author(s):  
Kamilah Adiva Freeman ◽  
Logan A. Yelderman
Keyword(s):  
Family Relationships ◽  
Academic Motivation ◽  
Well Being ◽  
Self Esteem ◽  
Future Research ◽  
Self Perception ◽  
Biological Father ◽  
Data Set ◽  
Familial Support ◽  
The Difference

The National Survey on American Life – Adolescent Supplemental data was designed to lay the foundation for future research in early identification of mental disorders for adults. The inclusion of social conditions adds to this detailed measure of mental health and provides a wealth of information that can be observed about mental well-being in adolescents. In particular, we used this data set to explore the interplay between self-perception and family relationships based on the absence of a biological father among African-American and Caribbean adolescents. This study provides a quantitative analysis of the difference between the perceived self and familial factors for those with a stepfather and those without a stepfather. As evident in the findings, those with a stepfather reported to have higher self-esteem, a more positive perception of self, and a more uplifting family model compared to those without a stepfather. These findings were detected by noting the significance values for a one-way ANOVA and observing the mean differences among the selected variables. Some discrepancy did exist, however; self-esteem with regards to education was reported to be lower for adolescents with a stepfather than without. This could be attributed to an overachievement mentality by those from single parent homes, alluding to the idea that adolescents without stepfathers possess intrinsic motivation and have the drive to attain a higher education. The data showed the presence of a father figure enhances self-perception and familial support, but not academic motivation.

scholarly journals Student ability assessment based on two IRT models

2005 ◽  
Vol 2 (2) ◽  
Author(s):  
Silvia Cagnone ◽  
Roberto Ricci
Keyword(s):  
Latent Variable ◽  
Real Data ◽  
Partial Credit Model ◽  
Theoretical Frameworks ◽  
Variable Model ◽  
Data Set ◽  
Advantages And Disadvantages ◽  
Graded Response ◽  
Student Ability ◽  
Problem Solving Process

The aim of this work is to analyze a part of the data collected in the Computer Science Department during the Informatics exams in the year 2003. Two different Item Response Theory models for ordered polytomous variables are considered in order to get an evaluation of student ability. Ordered polytomous variables are used for a problem solving process that contains a finite number of steps so that the ability of a student can be evaluated on the basis of the step achieved, namely, higher steps achieved are related to higher ability. The models considered are the Partial Credit Model and the Graded Response Model. The choice of these models has been dictated by the fact that although they are defined into different theoretical frameworks, the former belongs to the Rasch family (Masters, 1982) and the latter can be viewed as a Generalized Linear Latent Variable Model (Bartholomew and Knott, 1999), and hence they present different properties, both of them allow to treat ordinal observed variables. The analysis of the real data set through the two approaches allows to highlight their advantages and disadvantages.

scholarly journals Autonomous exploration of mobile robots through deep neural networks

2017 ◽  
Vol 14 (4) ◽  
pp. 172988141770357 ◽  
Author(s):  
Lei Tai ◽  
Shaohua Li ◽  
Ming Liu
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Mobile Robots ◽  
Visual Information ◽  
Latent Variable ◽  
Training Data ◽  
Variable Model ◽  
Data Set ◽  
Autonomous Exploration ◽  
Network Layers

The exploration problem of mobile robots aims to allow mobile robots to explore an unknown environment. We describe an indoor exploration algorithm for mobile robots using a hierarchical structure that fuses several convolutional neural network layers with decision-making process. The whole system is trained end to end by taking only visual information (RGB-D information) as input and generates a sequence of main moving direction as output so that the robot achieves autonomous exploration ability. The robot is a TurtleBot with a Kinect mounted on it. The model is trained and tested in a real world environment. And the training data set is provided for download. The outputs of the test data are compared with the human decision. We use Gaussian process latent variable model to visualize the feature map of last convolutional layer, which proves the effectiveness of this deep convolution neural network mode. We also present a novel and lightweight deep-learning library libcnn especially for deep-learning processing of robotics tasks.

Distinctive features of service performance measurement

2014 ◽  
Vol 34 (12) ◽  
pp. 1466-1486 ◽  
Author(s):  
Aki Jääskeläinen ◽  
Harri Laihonen ◽  
Antti Lönnqvist
Keyword(s):  
Performance Measurement ◽  
Empirical Studies ◽  
Service Operations ◽  
Service Performance ◽  
Current Status ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
Distinctive Features ◽  
Service Sectors

Purpose – The purpose of this paper is to study the distinctive features of service performance measurement. It also provides an overview of current status of performance measurement in three service sectors in Finland. Design/methodology/approach – The paper builds on two complementary empirical studies. In the first study, data were gathered through individual interviews in Finnish service organizations. In the second study, group interviews were held in order to enhance the understanding. The service sectors studied are knowledge-intensive, public and industrial services. There are two main units of analysis in the data set: an organization and service operations. Findings – The results show that the specific performance measurement characteristics are more apparent at service operations level. The findings reveal three distinctive features of service performance measurement. First, the contingency perspective stresses a need to consider the characteristics of different service contexts. Second, customer-orientation implies that the measurement should also cover customers’ actions during the service operation as well as the impacts of service operations. Third, the systemic perspective proposes that performance measurement should encompass all actors participating to service operations. Research limitations/implications – The results provide support for structuring the existing research and identifying paths for future research. They also assist practitioners in their search for best measurement practices. Originality/value – This paper contributes by providing empirical insights from three service sectors on the development needs of performance measurement. The findings provide understanding on what exactly makes service performance measurement problematic and suggests three paths to move forward.

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