Factor Analytic Approaches to Personality Item-Level Data

In order to examine its higher-order factor structure, we applied confirmatory factor and invariance analysis to item level data from the US standardization sample of the 16PF5, divided into a calibration sample (N = 5,130) and a validation sample (N = 5,131). Using standard assessments of model fit, all primary factors displayed good to excellent model fit, thus suggesting the scales to be broadly unidimensional. Results indicated a drop in model fit in both the structural and configurally invariant second order models, suggesting some level of misspecification in the global scales of Extraversion, Anxiety, Tough-Mindedness, Independence, and Self-Control. However, the degree of misspecification was slight. Overall, the analyses generally supported the proposed structure of the 16PF5.

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Greater than the Sum of Its Parts: δ can be Constructed from Item Level Data

Journal of Alzheimer s Disease ◽

10.3233/jad-150250 ◽

2015 ◽

Vol 49 (2) ◽

pp. 571-579 ◽

Cited By ~ 9

Author(s):

Donald R. Royall ◽

Raymond F. Palmer ◽

Teruyuki Matsuoka ◽

Yuka Kato ◽

Shogo Taniguchi ◽

...

Keyword(s):

Level Data ◽

Item Level

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Minding Your Ps and Qs: Going from Micro to Macro in Measuring Prices and Quantities

AEA Papers and Proceedings ◽

10.1257/pandp.20191004 ◽

2019 ◽

Vol 109 ◽

pp. 438-443

Author(s):

Gabriel Ehrlich ◽

John Haltiwanger ◽

Ron Jarmin ◽

David Johnson ◽

Matthew D. Shapiro

Keyword(s):

Census Bureau ◽

Alternative Methods ◽

Real Gdp ◽

Level Data ◽

Item Level ◽

National Output ◽

Level Of Aggregation ◽

Statistical Agencies ◽

High Level ◽

Bureau Of Labor Statistics

Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the promise of greatly improved key economic indicators along many dimensions.

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The vanity construct re-examined: LeBel's vanity scale

10.31219/osf.io/r5c28 ◽

2017 ◽

Author(s):

Etienne P. LeBel

Keyword(s):

Factor Structure ◽

Undergraduate Students ◽

Discriminant Validity ◽

General Purpose ◽

Item Pool ◽

Internal Reliability ◽

Factor Analytic ◽

Convergent And Discriminant Validity ◽

Personality Item ◽

Scale Data

A new vanity scale was developed according to a broader conceptualization, distinguishing between physical and intellectual vanity. The new scale was psychometrically validated using a total of 339 participants. Three studies were carried out using undergraduate students and family and friends. Validation procedures included assessing the convergent and discriminant validity of our scale using the Balanced Inventory of Desirable Responding (BIDR) and the International Personality Item Pool (IPIP). Internal reliability and factor analytic procedures were also performed on the scale data. Cumulative results of the three studies support the psychometric properties of the new scale. The final 22-item version of the scale showed high internal reliability and excellent factor structure. It is concluded that the scale may potentially be used for general purpose research to identify vain individuals.

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Associations between symptoms of problematic smartphone, Facebook, WhatsApp, and Instagram use: An item-level exploratory graph analysis perspective

Journal of Behavioral Addictions ◽

10.1556/2006.2020.00036 ◽

2020 ◽

Vol 9 (3) ◽

pp. 686-697 ◽

Cited By ~ 1

Author(s):

Dmitri Rozgonjuk ◽

Cornelia Sindermann ◽

Jon D. Elhai ◽

Alexander P. Christensen ◽

Christian Montag

Keyword(s):

Technology Use ◽

Network Models ◽

Survey Study ◽

Graph Analysis ◽

Bivariate Correlation ◽

Level Data ◽

Item Level ◽

German Speaking ◽

Cross Platform ◽

Smartphone Use

AbstractBackground and aimsStudies have demonstrated associations between both problematic smartphone and social networks use with everyday life adversities. However, examination of associations between problematic smartphone use (PSU) and problematic use of specific social networking platforms, especially on item-level data, has received relatively little attention. Therefore, the aim of the current study was to explore how items of problematic smartphone, Facebook, WhatsApp, and Instagram use are associated.Methods949 German-speaking adults participated in a web survey study. The participants were queried about their socio-demographics as well as levels of problematic smartphone, Facebook, WhatsApp, and Instagram use. In addition to bivariate correlation analysis, exploratory graph analysis (EGA), a type of network analysis, was conducted.ResultsThe results showed that while problematic Facebook and Instagram use seem to be distinct phenomena, problematic smartphone and WhatsApp use were heavily intertwined. Furthermore, the only cross-platform symptom observed was the extent of reported pain in wrists and neck due to digital technology use. The EGA network models showed very good stability in bootstrap analyses.Discussion and conclusionsIn general, the results of this study suggest that while Instagram and Facebook use may potentially constitute distinct problematic behaviors, problematic smartphone/WhatsApp use scales may be measuring highly similar or even the same construct.

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