Understanding and Using Factor Scores: Considerations for the Applied Researcher

DiStefano, Christine; Zhu, Min; Mîndrilă, Diana

doi:10.7275/da8t-4g52

Cited by 263 publications

(122 citation statements)

References 8 publications

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“…As far as multiple item variables as DSCHOOL, MONITOR, RELIGION, P_TOLER and PEER_USE are concerned; we summed the evaluations on each item of these factors. It is a simple but usual way to deal with this question in empirical research [43]. Subsequently, we obtain the membership evaluation of these variables by using a common procedure in fsQCA [41].…”

Section: Discussionmentioning

confidence: 99%

Explaining Cannabis Use by Adolescents in Tarragona (Spain): Correlational and Fuzzy Set Qualitative Comparative Analyses

Andrés-Sánchez¹,

Eraso²

2022

Preprint

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The literature on substance use usually extracts conclusions from data with correlational methods. Our study shows the usefulness of complementing ordered logistic regression (OLR) and fuzzy set qualitative comparative analysis (fsQCA) to assess factors inducing cannabis consumption in a sample of 1,935 teenagers. OLR showed a significant influence of gender (odd ratio (OR) =0.383, p<0.0001), parental monitoring (OR=0.587, p=0.0201); religiousness (OR=0.476, p=0.006); parental tolerance to substance use (OR=42.01, p<0.0001) and having close peers that consume substances (OR=5.60, p<0.0001). FsQCA has allowed fitting linkages between factors from a complementary perspective. (1) Coverage (cov) and consistency (cons) attained by solutions explaining use (cons=0.808, cov=0.357) are clearly lower than by recipes of non-use (cons=0.952, cov=0.869) (2) The interaction of gender, a tolerant family to use and the attitude toward substances by peers is very consistent to explain cannabis use. (3) The most important recipe explaining resistance to cannabis is simply parental disagreement with substance consumption (cons=0.956, cov=0.861) (4) Factors as gender, religiosity, parental monitoring and age show also a relevant impact on attitude toward cannabis use. However, whereas some of them impact symmetrically on use and non-use this does not follow in factors such as parental monitoring or age.

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Section: Discussionmentioning

confidence: 99%

Explaining Cannabis Use by Adolescents in Tarragona (Spain): Correlational and Fuzzy Set Qualitative Comparative Analyses

Andrés-Sánchez¹,

Eraso²

2022

Preprint

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“…The three factors with significant loadings in the four-factor analysis were the same as found with the three-factor EFA, and the strength of the loadings was similar. A non-refined weighted sum was used to compute factor scores, as described by DiStefano et al [24]. Performance parameters with loadings below 0.5 were excluded from the factor score.…”

Section: Discussionmentioning

confidence: 99%

Differentiating Motor Coordination in Children with Cerebral Palsy and Typically Developing Populations Through Exploratory Factor Analysis of Robotic Assessments

Dobri¹,

Samdup²,

Scott³

et al. 2021

2021 43rd Annual International Conference of the IEEE Engineering in Medicine &Amp; Biology Society (EMBC)

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General motor and executive functions are integral for tasks of daily living and are typically assessed when quantifying impairment of an individual. Robotic tasks offer highly repeatable and objective measures of motor and cognitive function. Additionally, robotic tasks and measures have been used successfully to quantify impairment of children with cerebral palsy (CP). Many robotic tasks include multiple performance parameters, so interpretation of results and identification of impairment can be difficult, especially when multiple tasks are completed. This study used exploratory factor analysis to investigate a potential set of quantitative models of motor and cognitive function in children, and compare performance of participants with CP to these models. The three calculated factors achieved strong differentiation between participants with mild CP and the typically developing population. This demonstrates the feasibility of these factors to quantify impairment and track improvements related to therapies.Clinical Relevance-This establishes a method to differentiate atypical motor performance related to CP using a robotic reversed visually guided reaching task.

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“…Second, to explore their factor structure, the ARHQ and AMHQ were each analyzed following steps previously taken in Welcome and Meza (2019 ; particularly for the ARHQ and the naming convention for its derived factors), which include: establishing the KMO (Kaiser–Meyer–Olkin) value of sampling adequacy, conducting the BTS (Bartlett’s Test of Sphericity) for suitability in capturing sample variance, visualizing scree plot to estimate the number of factors to extract, and performing maximum likelihood method with oblique rotation (direct oblimin) to derive the respective components, which were rendered through a regression-based approach to calculate factor scores ( Tabachnick and Fidell, 2007 ; DiStefano et al, 2009 ). Note that the directionality for the computed factor scores remain consistent with the directionality of the questions on each scale – that is, higher scores on any factors extracted from the ARHQ or AMHQ indicate, e.g., increased difficulties with learning to read or do simple arithmetic.…”

Section: Methodsmentioning

confidence: 99%

Tracking Familial History of Reading and Math Difficulties in Children’s Academic Outcomes

2022

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The current study aimed to investigate the extent to which familial history of reading and math difficulties have an impact on children’s academic outcomes within a 3-year longitudinal study, which evaluated their core reading and math skills after first (N = 198; 53% girls) and second grades (N = 166), as well as performance on complex academic tasks after second and third grades (N = 148). At baseline, parents were asked to complete the Adult Reading History Questionnaire (ARHQ) and its adaption, Adult Math History Questionnaire (AMHQ), to index familial history of reading and math difficulties, respectively. Preliminary findings established the psychometric properties of the AMHQ, suggesting that it is a reliable and valid scale. Correlation analyses indicated that the ARHQ was negatively associated with children’s reading skills, whereas the AMHQ was negatively related to math outcomes. Path results revealed that the ARHQ predicted children’s performance on complex reading tasks indirectly via their core reading skills, and the AMHQ was linked to complex math outcomes indirectly via core math abilities. The ARHQ was also found to be negatively correlated with measures of children’s math performance, with path findings suggesting that these relations were indirectly explained by differences in their core reading skills. These results suggest that assessing familial risk for academic difficulties may be crucial to understanding comorbid etiological and developmental associations between reading and math differences.

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Understanding and Using Factor Scores: Considerations for the Applied Researcher

Cited by 263 publications

References 8 publications

Explaining Cannabis Use by Adolescents in Tarragona (Spain): Correlational and Fuzzy Set Qualitative Comparative Analyses

Explaining Cannabis Use by Adolescents in Tarragona (Spain): Correlational and Fuzzy Set Qualitative Comparative Analyses

Differentiating Motor Coordination in Children with Cerebral Palsy and Typically Developing Populations Through Exploratory Factor Analysis of Robotic Assessments

Tracking Familial History of Reading and Math Difficulties in Children’s Academic Outcomes

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