Search results for "statistics"

Pokémon GO 2016: Exploring Situational Contexts of Critical Incidents in Augmented Reality

2016

Pokémon GO, an augmented reality mobile game, captured the attention of millions of people around the world in July 2016. Various sources from around the globe have reported both positive and negative incidents and outcomes related to the game. Some of the incidents have been particularly remarkable for the player, i.e., critical incidents. A critical incident is a single experience, which a person perceives or remembers as unusually positive or negative. Critical incidents typically are highly influential for human behaviour, and thus, important to study. Playing augmented reality games can take place in varying situational contexts. Situational context includes information that can be use…

Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations.

2014

Abstract: Information-theory procedures are powerful tools for multimodel inference and are now standard methods in ecology. When performing model averaging on a given set of models, the importance of a predictor variable is commonly estimated by summing the weights of models where the variable appears, the so-called sum of weights (SW). However, SWs have received little methodological attention and are frequently misinterpreted. We assessed the reliability of SW by performing model selection and averaging on simulated data sets including variables strongly and weakly correlated to the response variable and a variable unrelated to the response. Our aim was to investigate how useful SWs are …

A unifying framework for specifying generalized linear models for categorical data

2013

International audience; In the context of categorical data analysis, the case of nominal and ordinal data has been investigated in depth while the case of partially ordered data has been comparatively neglected. We first propose a new specification of generalized linear models (GLMs) for categorical response variables which en- compasses all the classical models such as multinomial logit, odds proportional or continuation ratio models but also led us to identify new GLMs. This unifying framework makes the different GLMs easier to compare and combine. We then define the more general class of partitioned conditional GLMs for categorical re- sponse variables. This new class enables to take int…

Recursion at the crossroads of sequence modeling, random trees, stochastic algorithms and martingales

2013

This monograph synthesizes several studies spanning from dynamical systems in the statistical analysis of sequences, to analysis of algorithms in random trees and discrete stochastic processes. These works find applications in various fields ranging from biological sequences to linear regression models, branching processes, through functional statistics and estimates of risk indicators for insurances. All the established results use, in one way or another, the recursive property of the structure under study, by highlighting invariants such as martingales, which are at the heart of this monograph, as tools as well as objects of study.

About time

2019

Purpose The purpose of this paper seeks to develop a motivation-based complementary framework for temporally dynamic user preferences to facilitate optimal timing in web personalisation. It also aims to highlight the benefits of considering user motivation when addressing issues in temporal dynamics. Design/methodology/approach Through theory, a complementary framework and propositions for motivation-based temporal dynamics for further testing are created. The framework is validated by feeding back findings, whereas some of the propositions are validated through an experiment. Findings The suggested framework distinguishes two ways (identifying/learning and shifting) of using a motive-base…

L'intérêt de la démarche prosopographique dans l'étude du mouvement communiste

2015

National audience

Multilevel Latent Profile Analysis With Covariates : Identifying Job Characteristics Profiles in Hierarchical Data as an Example

2018

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of th…

Multiple factor analysis: principal component analysis for multitable and multiblock data sets

2013

Analysis of the psicometric properties of a multiplication and division processes assessment scale

2019

Esta comunicación se encuentra disponible en la siguiente URL: http://www.infad.eu/RevistaINFAD/OJS/index.php/IJODAEP/article/view/1464/1321 Este número está dedicado a la "Psicología de la Educación y Saberes Originarios". The domain of multiplication and division operations depends on both algorithm management and the ability to identify the semantic structure of the problem and to translate it into mathematical language. Many students present difficulties in identifying the semantic structure of the problem but not applying the algorithm when the problem is presented numericaly. The aim of the study is to validate an assessment tool of the processes involved in multiplication and divisio…

Factor selection procedures in a Google Earthtm aided landslide susceptibility model: application to the Beiro river basin (Spain)

2011

A procedure to select the controlling factors connected to the slope instability has been defined. It allowed to assess the landslide susceptibility in the Rio Beiro basin (about 10 km2) over the north-eastern area of the city of Granada (Spain). Field and remote (Google EarthTM) recognition techniques allowed to generate a landslide inventory consisting in 127 phenomena. Univariate tests, using both association coefficients and validation results of single parameter susceptibility models, allowed to select among 15 controlling factors the ones that resulted as good predictor variables; these have been combined for unique conditions analysis and susceptibility maps were finally prepared. In…