Principal Component and Factor Analysis

Wheelwright, Matt; Levine, Zacharia; Garfinkel-Castro, Andrea; Bushman, Tracey; Brewer, Simon

doi:10.4324/9780429325038-5

Cited by 5 publications

(7 citation statements)

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“…Based on the three levels of willingness to socialize, we extracted the overall willingness to socialize using factor analysis (see Appendix D for details), where the scale reliability coe cient indicated that the three variables had high internal consistency reliability (Cronbach's alpha value of 0.914); the results of the factor analysis indicated that it was reasonable to extract a common factor that could explain 85.8% of the overall variance; and the KMO value was 0.72, indicating that using factor analysis was a reasonable approach for dimensionality reduction of the three variables (Wheelwright et al 2020). We adjusted the range of overall willingness to a score between 0 and 5, and the average score was 3.53.…”

Section: Variable Measurementmentioning

confidence: 99%

COVID-19 survivors: How pandemic precautions result in lingering discrimination in China

Guo

2022

Preprint

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As the pandemic continues worldwide, do coronavirus disease 2019 (COVID-19) survivors suffer social discrimination or prejudice? Existing scientific studies on COVID-19 survivors focus on the recovery of physical health while paying less attention to mental health and social integration. We investigated whether COVID-19 survivors suffer discrimination in China by examining representative social survey data with an embedded vignette experiment on social interaction in December 2021 during the lockdown in Xi'an (N = 3,046). We found that COVID-19 survivors suffered social discrimination and prejudice. Participants showed significantly lower willingness to socialize with hypothetical COVID-19 survivors. This discrimination effect was pronounced among individuals with high levels of education, social status, and social capital. This is partly due to the scarcity of public knowledge about COVID-19 recovery, which exacerbates the fear of infection in social interactions. Given China’s unique pandemic policies and media environment, the dissemination of information about COVID-19 recovery and risks is crucial, as is the provision of counselling to alleviate the depression and anxiety of COVID-19 survivors.

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Section: Variable Measurementmentioning

confidence: 99%

COVID-19 survivors: How pandemic precautions result in lingering discrimination in China

Guo

2022

Preprint

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“…In exact, the differences are mainly due to theoretical perspective. However, the question of data normality remains (Thomas, 1982;Wheelwright et al, Journal of Management Sciences 2020) as an important ingredient of FA.…”

Section: Is Fa An Appropriate Technique For Ls?mentioning

confidence: 99%

“…FA assumes that data are normally distributed albeit not a quintessential requirement (Tabachnick & Fidell, 2001;Wheelwright et al, 2020). Nevertheless, it is generally important for the validity of any parametric tests including FA that depend upon the extent to which the data are normally distributed.…”

Section: Normality Of Datamentioning

confidence: 99%

“…Most often it is an autonomous and independent Likert type question (Likert scale item) that a researcher is trying to analyze rather than data on LS (the scaled instrument) which is a reasoned and a structured whole. A LS composes of many items, at least 3 to 5measuring some single attitude using a set of questions (Wheelwright, Levine, Garfinkel-Castro, Bushman, & Brewer, 2020;Boone & Boone, 2012). Whereas questionnaires with only one item or question measuring an aspect of some attitude does by no means become a scale: it is just a question.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, the widespread use of FA on Likert Scale has made researchers think that it is perfectly valid to use FA on Likert Scale as it is used on any type of data (Brown, 2011;Wheelwright et al, 2020). It is even more unfortunate that even academic literature on LS itself is not spared of misunderstandings and misconceptions.…”

Section: Introductionmentioning

confidence: 99%

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Manualizing Factor Analysis of Likert Scale Data

Zaman¹,

Bibi²,

Sheikh³

et al. 2020

jms.2014

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Despite the academic value of factor analysis (FA) on Likert scale data, its statistical legality has been relentlessly questioned by professional statisticians. This article reviews relevant literature and proposes a statistically appropriate method of getting most out of FA on Likert scale. The review shows that a larger sample size is an important consideration in improving the appropriateness of FA on LS as it improves the solution in terms of normality, communalities and loadings. Further, a 7-9 point or greater scale to account for normality, an alpha level of 0.01 or 0.005, polychoric correlation instead of Pearson's are reported to improve the statistical appropriateness of the test of Likert scale. Moreover, using non-parametric alternatives like CATPCA to testify the results of FA greatly increased the overall value and validity of the test.

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Missing the Housing for the Trees: Equity in Urban Climate Planning

Angelo

MacFarlane

Sirigotis

et al. 2022

Journal of Planning Education and Research

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This paper examines equity’s incorporation into Climate Action Plans (CAPs), an increasingly important part of the urban sustainability planning landscape. We conduct a content analysis of 170 California CAPs and compare the plans’ treatment of equity to city characteristics such as size and income inequality. We find that equity language correlates with an increased presence of more systemic policy interventions, such as dense and/or affordable housing, in CAPs. However, the majority of CAPs “miss the housing for the trees,” with green policy agendas, such as trees and open space, remaining more dominant. We also find little association between local inequalities and how CAPs incorporate equity goals.

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Principal Component and Factor Analysis

Cited by 5 publications

References 0 publications

COVID-19 survivors: How pandemic precautions result in lingering discrimination in China

COVID-19 survivors: How pandemic precautions result in lingering discrimination in China

Manualizing Factor Analysis of Likert Scale Data

Missing the Housing for the Trees: Equity in Urban Climate Planning

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