Analiza vremena reakcije modelovanjem linearnih mešovitih efekata

Radanović, Jelena; Vaci, Nemanja

doi:10.19090/pp.2013.3.311-332

Cited by 3 publications

(1 citation statement)

References 45 publications

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“…Dodatna prednost ovog metoda je što omogućava kontrolu drugih izvora varijabilnosti sadržanih u vremenu reakcije. Mi smo se odlučili za varijansu ispitanika i stimulusa, što predstavlja tipičan izbor za ovu vrstu zavisne varijable (Radanović i Vaci, 2013) i nacrta (Barr, 2013). Za procenu kvaliteta modela i odabir konačnog modela obrade, korišćeni su AIC 5 i BIC 6 koeficijenti i test Ln verodostojnosti.…”

Section: Analiza Rezultataunclassified

Uloga Oblika I Boje U Prepoznavanju I Klasifikaciji Poznatih Vizuelnih Objekata

Ludajić

Zdravković

2016

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Čulom vida dobija se veliki broj informacija na osnovu kojih je moguće prepoznati objekte (npr. boja, oblik, tekstura, 3D struktura, pokret, pravac kretanja). Količina informacija nije samo velika već se i tiče različitih aspekata objekata, te je nakon prepoznavanja neophodna i klasifikacija, tj. grupisanje i integrisanje ulaznih informacija (Marr, 1982). Zbog svega ovoga prepoznavanje i klasifikacija spadaju u osnovne kognitivne procese koji omogućavaju saznavanje sveta oko nas, a istraživanju načina na koji naš sistem realizuje pomenute kognitivne procese posvećen je veliki broja studija

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Section: Analiza Rezultataunclassified

Uloga Oblika I Boje U Prepoznavanju I Klasifikaciji Poznatih Vizuelnih Objekata

Ludajić

Zdravković

2016

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Chess databases as a research vehicle in psychology: Modeling large data

Vaci

Bilalić

2016

Behav Res

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The game of chess has often been used for psychological investigations, particularly in cognitive science. The clear-cut rules and well-defined environment of chess provide a model for investigations of basic cognitive processes, such as perception, memory, and problem solving, while the precise rating system for the measurement of skill has enabled investigations of individual differences and expertise-related effects. In the present study, we focus on another appealing feature of chess—namely, the large archive databases associated with the game. The German national chess database presented in this study represents a fruitful ground for the investigation of multiple longitudinal research questions, since it collects the data of over 130,000 players and spans over 25 years. The German chess database collects the data of all players, including hobby players, and all tournaments played. This results in a rich and complete collection of the skill, age, and activity of the whole population of chess players in Germany. The database therefore complements the commonly used expertise approach in cognitive science by opening up new possibilities for the investigation of multiple factors that underlie expertise and skill acquisition. Since large datasets are not common in psychology, their introduction also raises the question of optimal and efficient statistical analysis. We offer the database for download and illustrate how it can be used by providing concrete examples and a step-by-step tutorial using different statistical analyses on a range of topics, including skill development over the lifetime, birth cohort effects, effects of activity and inactivity on skill, and gender differences.

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Large data and Bayesian modeling—aging curves of NBA players

et al. 2019

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Researchers interested in changes that occur as people age are faced with a number of methodological problems, starting with the immense time scale they are trying to capture, which renders laboratory experiments useless and longitudinal studies rather rare. Fortunately, some people take part in particular activities and pastimes throughout their lives, and often these activities are systematically recorded. In this study, we use the wealth of data collected by the National Basketball Association to describe the aging curves of elite basketball players. We have developed a new approach rooted in the Bayesian tradition in order to understand the factors behind the development and deterioration of a complex motor skill. The new model uses Bayesian structural modeling to extract two latent factors, those of development and aging. The interaction of these factors provides insight into the rates of development and deterioration of skill over the course of a player’s life. We show, for example, that elite athletes have different levels of decline in the later stages of their career, which is dependent on their skill acquisition phase. The model goes beyond description of the aging function, in that it can accommodate the aging curves of subgroups (e.g., different positions played in the game), as well as other relevant factors (e.g., the number of minutes on court per game) that might play a role in skill changes. The flexibility and general nature of the new model make it a perfect candidate for use across different domains in lifespan psychology.

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Analiza vremena reakcije modelovanjem linearnih mešovitih efekata

Cited by 3 publications

References 45 publications

Uloga Oblika I Boje U Prepoznavanju I Klasifikaciji Poznatih Vizuelnih Objekata

Uloga Oblika I Boje U Prepoznavanju I Klasifikaciji Poznatih Vizuelnih Objekata

Chess databases as a research vehicle in psychology: Modeling large data

Large data and Bayesian modeling—aging curves of NBA players

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