scholarly journals THIS (METHOD) IS (NOT) FINE

2018 ◽  
Vol 50 (6) ◽  
pp. 872-874
Author(s):  
Jelte M. Wicherts
Keyword(s):  
Recent Article ◽  
Sampling Error ◽  
Level Data ◽  
Item Level ◽  
Restriction Of Range

SummaryIn their response to my criticism of their recent article in Journal of Biosocial Science (te Nijenhuis et al., 2017), te Nijenhuis and van den Hoek (2018) raise four points none of which concerns my main point that the method of correlated vectors (MCV) applied to item-level data represents a flawed method. Here, I discuss te Nijenhuis and van den Hoek’s four points. First, I argue that my previous application of MCV to item-level data showed that the method can yield nonsensical results. Second, I note that meta-analytic corrections for sampling error, imperfect measures, restriction of range and unreliability of the vectors are futile and cannot help fix the method. Third, I note that even with perfect data, the method can yield negative correlations. Fourth, I highlight the irrelevance of te Nijenhuis and van den Hoek (2018)’s point that my comment had not been published in a peerreviewed journal by referring to my articles in 2009 and 2017 on MCV in peer-reviewed journals.

scholarly journals An Investigation of the Factor Structure of the 16PF, Version 5

2014 ◽  
Vol 35 (1) ◽  
pp. 38-46 ◽  
Author(s):  
Paul Irwing ◽  
Tom Booth ◽  
Mark Batey
Keyword(s):  
Factor Structure ◽  
Self Control ◽  
Model Fit ◽  
Validation Sample ◽  
Level Data ◽  
Calibration Sample ◽  
Confirmatory Factor ◽  
Item Level ◽  
The Us ◽  
Order Factor

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.

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

2015 ◽  
Vol 49 (2) ◽  
pp. 571-579 ◽  
Author(s):  
Donald R. Royall ◽  
Raymond F. Palmer ◽  
Teruyuki Matsuoka ◽  
Yuka Kato ◽  
Shogo Taniguchi ◽  
...  
Keyword(s):  
Level Data ◽  
Item Level

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

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.

Estimating acorn crops using visual surveys

1994 ◽  
Vol 24 (10) ◽  
pp. 2105-2112 ◽  
Author(s):  
Walter D. Koenig ◽  
Johannes M.H. Knops ◽  
William J. Carmen ◽  
Mark T. Stanback ◽  
Ronald L. Mumme
Keyword(s):  
High Efficiency ◽  
Sampling Error ◽  
Population Variation ◽  
Conifer Species ◽  
Acorn Production ◽  
Visual Survey ◽  
Annual Productivity ◽  
Level Data ◽  
Survey Technique ◽  
Individual Trees

We describe a visual survey technique for evaluating acorn production. In contrast with previously proposed methods, our technique yields ratio-level data on annual productivity that are analyzable with standard statistics and, by sampling the same trees each year, data on the reproductive patterns of individual trees. We compared this technique with two independent sets of acorn-trap data acquired on oaks of three species at Hastings Reservation in central coastal California. Correlations between acorns counted by the visual surveys and collected from acorn traps under the same trees were significant for all three species. Most scatter in the data appeared to be attributable to three causes: (1) sampling error, especially among trees with very small crops, (2) finite counting speed, leading to a lack of discrimination among trees with very large crops by the visual surveys, and (3) arboreal acorn removal by animals. This latter factor can be particularly large, rendering visual surveys more reliable than the use of traps. Furthermore, only the high efficiency of visual surveys allows for the practical assessment of samples large enough to accommodate high within-population variation and detect widespread geographic variation in acorn production. Visual surveys offer a method of assessing the fruit or cone crops of many hardwood and conifer species that is not only more efficient but also more accurate than the use of traps.

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

2020 ◽  
Vol 9 (3) ◽  
pp. 686-697 ◽  
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.

Factor Analytic Approaches to Personality Item-Level Data

1997 ◽  
Vol 68 (3) ◽  
pp. 561-589 ◽  
Author(s):  
A.T. Panter ◽  
Kimberly A. Swygert ◽  
W. Grant Dahlstrom ◽  
J.S. Tanaka
Keyword(s):  
Factor Analytic ◽  
Level Data ◽  
Item Level ◽  
Personality Item

Multiple imputation was an efficient method for harmonizing the Mini-Mental State Examination with missing item-level data

2011 ◽  
Vol 64 (7) ◽  
pp. 787-793 ◽  
Author(s):  
Richard A. Burns ◽  
Peter Butterworth ◽  
Kim M. Kiely ◽  
Allison A.M. Bielak ◽  
Mary A. Luszcz ◽  
...  
Keyword(s):  
Multiple Imputation ◽  
Efficient Method ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Level Data ◽  
Item Level ◽  
Missing Item ◽  
State Examination

scholarly journals Aggressive behaviour in childhood and adolescence: the role of smoking during pregnancy, evidence from four twin cohorts in the EU-ACTION consortium

2018 ◽  
Vol 49 (4) ◽  
pp. 646-654 ◽  
Author(s):  
Margherita Malanchini ◽  
Emily Smith-Woolley ◽  
Ziada Ayorech ◽  
Kaili Rimfeld ◽  
Eva Krapohl ◽  
...  
Keyword(s):  
Aggressive Behaviour ◽  
Meta Analysis ◽  
Independent Effect ◽  
Childhood And Adolescence ◽  
Perinatal Factors ◽  
Smoking During Pregnancy ◽  
Level Data ◽  
Item Level ◽  
Socio Demographic Factors ◽  
The Eu

AbstractBackgroundMaternal smoking during pregnancy (MSDP) has been linked to offspring's externalizing problems. It has been argued that socio-demographic factors (e.g. maternal age and education), co-occurring environmental risk factors, or pleiotropic genetic effects may account for the association between MSDP and later outcomes. This study provides a comprehensive investigation of the association between MSDP and a single harmonized component of externalizing: aggressive behaviour, measured throughout childhood and adolescence.MethodsData came from four prospective twin cohorts – Twins Early Development Study, Netherlands Twin Register, Childhood and Adolescent Twin Study of Sweden, and FinnTwin12 study – who collaborate in the EU-ACTION consortium. Data from 30 708 unrelated individuals were analysed. Based on item level data, a harmonized measure of aggression was created at ages 9–10; 12; 14–15 and 16–18.ResultsMSDP predicted aggression in childhood and adolescence. A meta-analysis across the four samples found the independent effect of MSDP to be 0.4% (r = 0.066), this remained consistent when analyses were performed separately by sex. All other perinatal factors combined explained 1.1% of the variance in aggression across all ages and samples (r = 0.112). Paternal smoking and aggressive parenting strategies did not account for the MSDP-aggression association, consistent with the hypothesis of a small direct link between MSDP and aggression.ConclusionsPerinatal factors, including MSDP, account for a small portion of the variance in aggression in childhood and adolescence. Later experiences may play a greater role in shaping adolescents’ aggressive behaviour.

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