Exploratory factor analysis revealing complex structure

Ertel, Suitbert

doi:10.1016/j.paid.2010.09.026

Cited by 15 publications

(7 citation statements)

References 12 publications

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“…The structure d in Figure 1 consists exclusively of complex structure items. The term complex structure has recently been revitalized by Ertel (2009, 2011). He developed the varimin rotation of factors, which forces each item to express an equal amount of each dimension.…”

Section: The Circumplex Modelmentioning

confidence: 99%

Reliability of Circumplex Axes

2013

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We present a confirmatory factor analysis (CFA) procedure for computing the reliability of circumplex axes. The tauequivalent CFA variance decomposition model estimates five variance components: general factor, axes, scale-specificity, block-specificity, and item-specificity. Only the axes variance component is used for reliability estimation. We apply the model to six circumplex types and 13 instruments assessing interpersonal and motivational constructs-Interpersonal Adjective List Groups (behavioral adjectives; SYMLOG)-in 17 German-speaking samples (29 subsamples, grouped by self-report, other report, and metaperception assessments). The general factor accounted for a proportion ranging from 1% to 48% of the item variance, the axes component for 2% to 30%; and scale specificity for 1% to 28%, respectively. Reliability estimates varied considerably from .13 to .92. An application of the Nunnally and Bernstein formula proposed by Markey, Markey, and Tinsley overestimated axes reliabilities in cases of large-scale specificities but otherwise works effectively. Contemporary circumplex evaluations such as Tracey's RANDALL are sensitive to the ratio of the axes and scale-specificity components. In contrast, the proposed model isolates both components.

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Section: The Circumplex Modelmentioning

confidence: 99%

Reliability of Circumplex Axes

2013

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“…Searches for such factors have relied on the sports performance analysis generally used in studies regarding both individual and combined events [11,12,13,14,15,16,17,18,19,20,34,35,36,37].…”

Section: Discussionmentioning

confidence: 99%

“…Literature regarding decathlon includes papers where the structure of the event is explored and the types of the most successful athlete types are identified e.g. based on factor analysis [13,14], hierarchical cluster analysis [15], configural frequency analysis [16], LVMs (semiparametric latent variable models) [12] and other [17].…”

Section: Introductionmentioning

confidence: 99%

Principal Component Analysis in the Study of the Structure of Decathlon at Different Stages of Sports Career

Dziadek

Iskra

Mendyka

et al. 2022

Polish Journal of Sport and Tourism

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Introduction. Due to the complexity of decathlon resulting from the number and diversity of the component events as well as difficult and time-consuming training required of athletes, high sports performance in this combined form of competition may depend on several factors. Material and Methods. The objective of the paper was to subject the careers of the world’s top decathletes competing between 1985 and 2018 to the principal component analysis (PCA) in order to explore and define interdependencies between the component events and the final result in decathlon at four stages of sports career development (from U20 – junior, through U23 and athletic excellence stage to decline in athletic performance). Results. The results made it possible to define the majority of the principal components determining high performance in decathlon. Conclusions. The analysis has shown that each sports ontogenesis stage has shared elements and a specific arrangement of events for every age category.

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“…Currently, there are also works, in which advanced calculation methods (e.g. factor analysis, configural frequency analysis) were used to define the type of competitors which are successful in decathlon because of their aptitude and motor skills (Bilić, 2015;Stemmler, Bäumler, 2005), as well as to study the hidden structure of decathlon (Ertel, 2011). Park, Zatsiorsky (2011) in their work used the principal component analysis (PCA) to designate new variables describing the structure of decathlon on the basis of the results of competitors competing during Olympic Games in years 1988-2008.…”

Section: Introductionmentioning

confidence: 99%

Principal Component Analysis in the Study of Structure of the Best Polish Decathlon Competitors from the Period between 1985–2015

Dziadek

Iskra

Przednówek

2018

Central European Journal of Sport Sciences and Medicine

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The modern decathlon is a sport consisting of ten different events held over two days, played by men. Depending on the complexity of combined events, variety of events (runs, throws, jumps), the multi-stage, time-consuming and difficult training process the sport is considered as one of the most difficult. The analysis of careers of the best decathlon participants and applying advanced data-mining methods can help define the patterns occurring between each decathlon event and the final result. The research material encompasses career data of the 25 top competitors from Poland in years 1985-2015. Principal component analysis (PCA) was used in the research in order to designate new uncorrelated variables (components), representing input data across a new plane. Data analysis involved appointment of correlations between the events, determining the number of main components taken into account in further studies, analysis of the weight of each variable in formation of main components as well as visualisation and interpretation of results in the new plane described by the determined main components. Through the implementation of PCA method in the process of analysis it was possible to designate over 69% of compound data volatility with the use of the first three components. The first component, comprised of seven variables, displays the largest share in the total variability. The study of the relationship between variables in the new plane displayed strong correlations between sprint events (100 m, 110 m hurdles) and long jump and pole vault. No correlations between the 1,500 m run and other events were found.

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Exploratory factor analysis revealing complex structure

Cited by 15 publications

References 12 publications

Reliability of Circumplex Axes

Reliability of Circumplex Axes

Principal Component Analysis in the Study of the Structure of Decathlon at Different Stages of Sports Career

Principal Component Analysis in the Study of Structure of the Best Polish Decathlon Competitors from the Period between 1985–2015

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