Reconstructing Adulthood: Revising the Markers of Adulthood Scale for Increased Ecological Validity

2021 ◽  
pp. 003329412110617
Author(s):  
Kaley B. Norman ◽  
Jon E. Grahe ◽  
Seungyeon Lee
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Transition To Adulthood ◽  
Ecological Validity ◽  
Principal Component ◽  
Future Directions ◽  
Role Transitions ◽  
Demographic Survey ◽  
Best Fit

Young adults endorse more individualistic and internal adulthood milestones compared to prior generations. Arnett (1994) introduced the Markers of Adulthood (MoA) scale to capture this shift in the transition to adulthood using 38 markers associated with becoming an adult, including marriage, having children, and living independently. These items were based on psychological, anthropological, and sociological determinations concerning adulthood, and were arranged into subscales based on their theoretical association rather than statistical analysis. Since the scale was introduced, researchers have addressed crucial questions about the validity of the MoA scale’s milestones. A recurring theme was identifying items that could be sorted into reliable subscales. We examined a collection of original items and included new ones, such as “have a professional social media account” and “recognize personal capabilities and shortcomings” to configure a revised MoA model. A total of 861 participants in seven national locations responded to a demographic survey, the Inventory of the Dimensions of Emerging Adulthood (IDEA; Reifman, et al., 2007), and a collection of MoA items. We conducted a principal component analysis to identify 22 items and four factors (role transitions, independence, legality markers, and relative maturity) which represented 55% of the total variance in the dataset. All factors except legality markers were identified by prior researchers. While four factors demonstrated the best fit for subscale configurations, the revised MoA was considered most reliable when used in its entirety. Our examination ends with a discussion of future directions for configuring items which may produce reliable subscales.

Reconstructing Adulthood: Revising the Markers of Adulthood Scale for Increased Ecological Validity

2020 ◽  
Author(s):  
Kaley Norman ◽  
Jon E. Grahe ◽  
Seungyeon Lee
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Transition To Adulthood ◽  
Ecological Validity ◽  
Principal Component ◽  
Future Directions ◽  
Role Transitions ◽  
Demographic Survey ◽  
Best Fit

Young adults endorse more individualistic and internal adulthood milestones compared to prior generations. Arnett (1994) introduced the Markers of Adulthood (MoA) scale to capture this shift in the transition to adulthood using 38 markers associated with becoming an adult, including marriage, having children, and living independently. These items were based on psychological, anthropological, and sociological determinations concerning adulthood, and were arranged into subscales based on their theoretical association rather than statistical analysis. Since the scale was introduced, researchers have addressed crucial questions about the validity of the MoA scale’s milestones. A recurring theme was identifying items that could be sorted into reliable subscales. We examined a collection of original items and included new ones, such as “have a professional social media account” and “recognize personal capabilities and shortcomings” to configure a revised MoA model. A total of 861 participants in seven national locations responded to a demographic survey, the Inventory of the Dimensions of Emerging Adulthood (IDEA; Reifman, et al., 2007), and a collection of MoA items. We conducted a principal component analysis (PCA) to identify 22 items and four factors (role transitions, independence, legality markers, and relative maturity) which represented 55% of the total variance in the dataset. All factors except legality markers were identified by prior researchers. While four factors demonstrated the best fit for subscale configurations, the revised MoA was considered most reliable when used in its entirety. Our examination ends with a discussion of future directions for configuring items which may produce reliable subscales.

Assessing Teacher Manageability: A Factor Analytic Approach

1988 ◽  
Vol 13 (4) ◽  
pp. 245-252 ◽  
Author(s):  
Stephen P. Safran ◽  
Joan S. Safran ◽  
Robert S. Barcikowski
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Problem Behaviors ◽  
Principal Component ◽  
Analytic Approach ◽  
Future Research ◽  
Maladaptive Behaviors ◽  
Varimax Rotation ◽  
Behaviorally Disordered ◽  
Factor Analytic

An ecologically valid appraisal of students' problem behaviors must include assessment of the teacher's role as perceiver on various levels. This study analyzes the teacher manageability construct, examining educators' beliefs about their ability to manage 39 generally maladaptive behaviors within their own classroom. To address measurement limitations of previous investigations (including nonfactor analytic clustering of behaviors), a principal component analysis followed by a varimax rotation was administered on teacher manageability ratings (N = 182). This statistical analysis yielded nine component subtests (the Teacher Manageability Scale) and demonstrated that by changing the method used to group behaviors, you also modify the structure of a teacher checklist. Lack of Communication was identified as the most difficult behavior to manage. Implications for professionals working with students identified as behaviorally disordered and for future research are discussed.

scholarly journals Statistical Analysis of Mitochondrial Pathologies in Childhood: Identification of Deficiencies Using Principal Component Analysis

2000 ◽  
Vol 80 (7) ◽  
pp. 1019-1030 ◽  
Author(s):  
Thierry Letellier ◽  
Gilles Durrieu ◽  
Monique Malgat ◽  
Rodrigue Rossignol ◽  
Jaromir Antoch ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Component Analysis

A Cross-Cultural Perspective on Motives and Patterns of Brand Recommendation in Social Media

2018 ◽  
Vol 8 (2) ◽  
pp. 27-44 ◽  
Author(s):  
Castulus Kolo ◽  
Stefan Widenhorn ◽  
Anna-Lena Borgstedt ◽  
David Eicher
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Cultural Differences ◽  
Formal Education ◽  
Principal Component ◽  
Cross Cultural ◽  
Substantial Influence ◽  
Cultural Perspective ◽  
The Us ◽  
Do So

This article describes how today, social media enable users to comment on brands in a multitude of ways. Although it is undoubted that this can have a substantial influence on the way brands impact on consumers, comparatively little is known about what motivates consumers to recommend brands in social media and whether there are cultural differences therein. This article aims to determine the factors leading to either positive or negative communication about brands on Facebook, YouTube, Twitter, and brand-related blogs based on a representative sample from Germany and the US, each with 1,000 adults. Complementary to an analysis of factors determining a general inclination to recommend, a principal component analysis of the diverse motives to do so exhibits patterns being largely consistent in a cross-cultural perspective, however, with differences in specific practices concerning gender, age, and formal education. A cluster analysis as well as taking a look at “influencers” provide a basis for developing differentiated strategies of brand communication and management respectively.

scholarly journals Fibre attributes and mapping the cultivar influence of different industrial cellulosic crops (cotton, hemp, flax, and canola) on textile properties

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ikra Iftekhar Shuvo
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Textile Fibre ◽  
Two Dimensional ◽  
Production Engineering ◽  
Hemp Fibres ◽  
Likelihood Analysis ◽  
Microscopic Studies ◽  
And Function

Abstract Natural lignocellulosic fibres (NLF) extracted from different industrial crops (like cotton, hemp, flax, and canola) have taken a growing share of the overall global use of natural fibres required for manufacturing consumer apparels and textile substrate. The attributes of these constituent NLF determine the end product (textiles) performance and function. Structural and microscopic studies have highlighted the key behaviors of these NLF and understanding these behaviors is essential to regulate their industrial production, engineering applications, and harness their benefits. Breakthrough scientific successes have demonstrated textile fibre properties and significantly different mechanical and structural behavioral patterns related to different cultivars of NLF, but a broader agenda is needed to study these behaviors. Influence of key fibre attributes of NLF and properties of different cultivars on the performance of textiles are defined in this review. A likelihood analysis using scattergram and Pearson’s correlation followed by a two-dimensional principal component analysis (PCA) to single-out key properties explain the variations and investigate the probabilities of any cluster of similar fibre profiles. Finally, a Weibull distribution determined probabilistic breaking tenacities of different fibres after statistical analysis of more than 60 (N > 60) cultivars of cotton, canola, flax, and hemp fibres.

scholarly journals Principal Component Analysis of Multiwavelength Properties of Seyfert Galaxies

1994 ◽  
Vol 159 ◽  
pp. 502-502
Author(s):  
Deborah Dultzin–Hacyan ◽  
Carlos Ruano
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Seyfert Galaxies ◽  
Component Analysis ◽  
X Ray ◽  
Radio Data

A multidimensional statistical analysis of observed properties of Seyfert galaxies has been carried out using Principal Component Analysis (PCA) applied to X-ray, optical, near and far IR and radio data for all the Seyfert galaxies types 1 and 2 for the catalog by Lipovtsky et al. (1987).

scholarly journals Statistical Study of Variability in Rainfall and Analysis of Etreme Rainfall Events for Hill Stations of Uttarakhand

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Bimal Pande ◽  
Sneh Joshi ◽  
Seema Pande
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Statistical Study ◽  
Parametric Method ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Component Analysis ◽  
Rainfall Pattern ◽  
Composite Matrix ◽  
Rainfall Events

Statistical analysis of rainfall pattern and its variability for 20 years (1990-2010) data is performed for two mountainous urban centres of Uttarakhand i.e. Almora (29.60 N, 79.670 E and altitude 1,204m asl) and Nainital (29.40 N, 79.470 E and altitude 2,020m asl). Non Parametric method of Principal Component Analysis (PCA) gives the correlation between different extreme rainfall indices. It is concluded that PCA suggest 90% of the variance in composite matrix of extreme rainfall indices.

scholarly journals Chemical Composition and Variability of Leaf and Berry oils from Corsican Juniperus macrocarpa

2018 ◽  
Vol 13 (2) ◽  
pp. 1934578X1801300
Author(s):  
Joséphine Ottavioli ◽  
Ange Bighelli ◽  
Joseph Casanova ◽  
Félix Tomi
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Chemical Composition ◽  
Principal Component ◽  
Component Analysis ◽  
Germacrene D ◽  
Leaf Oil ◽  
Main Components ◽  
Main Component ◽  
C Nmr

The chemical composition of five leaf oil samples and eighteen berry oil samples from Corsican Juniperus macrocarpa have been investigated by GC(RI), GC-MS and 13C NMR. The composition of berry oils was dominated by monoterpene hydrocarbons with α-pinene (56.4-78.9%) as main component followed by myrcene (2.2-11.9%). Germacrene D (4.5-103%) was the major sesquiterpene. The contents of the main components of leaf oils varied drastically from sample to sample: α-pinene (28.7-76.4%), δ3-carene (up to 17.3%), β-phellandrene (up to 12.3%), manoyl oxide (up to 8.1%). The occurrence of the unusual ( Z)-pentadec-6-en-2-one (0.1-1.2%) should be pointed out. Statistical analysis (Principal Component Analysis and k- means partition) suggested a unique group with atypical samples.

A Cross-Cultural Perspective on Motives and Patterns of Brand Recommendation in Social Media

2019 ◽  
pp. 388-406
Author(s):  
Castulus Kolo ◽  
Stefan Widenhorn ◽  
Anna-Lena Borgstedt ◽  
David Eicher
Keyword(s):  
Social Media ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Cultural Differences ◽  
Formal Education ◽  
Principal Component ◽  
Cross Cultural ◽  
Substantial Influence ◽  
Cultural Perspective ◽  
The Us

This article describes how today, social media enable users to comment on brands in a multitude of ways. Although it is undoubted that this can have a substantial influence on the way brands impact on consumers, comparatively little is known about what motivates consumers to recommend brands in social media and whether there are cultural differences therein. This article aims to determine the factors leading to either positive or negative communication about brands on Facebook, YouTube, Twitter, and brand-related blogs based on a representative sample from Germany and the US, each with 1,000 adults. Complementary to an analysis of factors determining a general inclination to recommend, a principal component analysis of the diverse motives to do so exhibits patterns being largely consistent in a cross-cultural perspective, however, with differences in specific practices concerning gender, age, and formal education. A cluster analysis as well as taking a look at “influencers” provide a basis for developing differentiated strategies of brand communication and management respectively.

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