Measurement invariance in comparative Internet use research

Büchi, Moritz

doi:10.1016/j.scoms.2016.03.003

Cited by 6 publications

(8 citation statements)

References 51 publications

(60 reference statements)

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“…Measurement invariance (equivalence) concerns whether scores from the operationalization of a construct have the same meaning under different conditions (Kline, 2016). Compared to the most commonly used multi‐group confirmatory factor analysis, which focuses on measurement model across samples, MGSEM additionally incorporates structural modeling (Büchi, 2016).…”

Section: Methodsmentioning

confidence: 99%

“…The current study is concerned with whether motivational factors, as a latent factor, are measured by the same constructs of creativity motivation, creative confidence, and creative growth‐mindset across different country groups. Configural invariance is imperative here because it allows the exploration of the basic structure of the measurement model cross‐nationality (Büchi, 2016). If the measurement models are ensured to have similar patterns across groups, the next restriction level is metric invariance .…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Social Environmental Factors and Personal Motivational Factors Associated with Creative Achievement: A Cross‐Cultural Perspective

Zhang

Hoxha

Aljughaiman

et al. 2020

Journal of Creative Behavior

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Although the theory of the socio‐cultural approach to creativity is gaining steam, empirical studies with advanced statistical tools are lagging behind. To address the gap of empirical studies integrating individual, social environmental, and cultural factors, we examined how motivational factors and environmental responsiveness were jointly related to college students’ creative achievement in different nations. Participants were university students from eight culturally and geographically diverse regions: Argentina, Austria, Chile, China, Kosovo, Russia, Saudi Arabia, and Turkey. Overall, the results painted a generally positive picture of the relationship between environmental responsiveness, motivational factors, and creative achievement. By employing structural equation modeling (SEM) and multiple‐group SEM (MGSEM) methods, results partially supported the mediation role of motivational factors between environmental responsiveness and creative achievement. In addition, we observed more consistent relationships between parental responsiveness and motivational factors or creative achievement, than lecturer. This held in common across all seven countries which fulfilled the requirements for the SEM process, indicating that parents play a potential vital role in supporting students’ motivational aspects and creative achievements, whereas lecturers supporting role is relative to the cultural organizational circumstances. As the first large‐scale empirical study with a socio‐cultural approach, we invited further discussion and proposed future cross‐cultural research of this kind. Research implications and practical suggestions were addressed.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Social Environmental Factors and Personal Motivational Factors Associated with Creative Achievement: A Cross‐Cultural Perspective

Zhang

Hoxha

Aljughaiman

et al. 2020

Journal of Creative Behavior

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“…Some types of comparative analyses and benchmark research on digital inequalities would certainly benefit from a single skill score (Dolni car, Prevodnik, and Vehovar 2014). However, calculating a single summative score would be possible only if the short version of the ISS were found to be a valid second-order construct (Brown 2015). Therefore: RQ4: Does the short version of the ISS measure internet skills as a second-order construct?…”

Section: Rq3: Does the Short Version Of The Iss Demonstrate Measurement Equivalence Between Younger And Older Internet Users?mentioning

confidence: 99%

“…The results of the first-order CFA showed adequate construct validity of the ISS, while indicating the viability of a measurement model with four first-level factors and one second-level factor because of the pattern of correlations (h matrix) among the four first-order factors (Table 5). To answer RQ4, a CFA second-order measurement model of the ISS was specified (see Figure 1) and analyzed, using a three-stage approach devised by Brown (2015).…”

Section: Confirmatory Factor Analysismentioning

confidence: 99%

Measuring internet skills in a general population: A large-scale validation of the short Internet Skills Scale in Slovenia

Grosĕlj

Deursen

Dolničar

et al. 2021

The Information Society

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This study assessed the construct and criterion validity of the short version of the Internet Skills Scale and examined whether its four dimensions -Operational, Information Navigation, Social, and Creative skillsare influenced by a higher-order dimension of general internet skills as one second-order factor. In 2018, a face-to-face survey comprising of the 20-item Internet Skills Scale and 22 other items related to digital inclusion was conducted in a sample of 814 internet users in Slovenia. The results of exploratory and confirmatory factor analyses, as well as other multivariate methods, showed that the Internet Skills Scale is characterized by high to adequate convergent and divergent validity. Acceptable criterion validity was observed for Operational and Information Navigation skills. In terms of measurement invariance, the data supported configural and metric invariance, whereas the scalar invariance was not fully confirmed, suggesting that older adults' lower scores on the Creative skills items were not related to lower levels of internet skills in the same way as they were among younger individuals. Last, the results provided original evidence of the Internet Skills Scale as a second-order construct, meaning that a single summative Internet Skills Scale score could be created as an adequate measure of an individual's internet skills.

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“…But even in this project which was designed with a comparative goal from the outset, meaningful conclusions can only be drawn after careful tests of measurement invariance (see Büchi, 2016). And the same applies to comparative research based on content analyses; here similar tests of measurement equivalence can be conducted (Wirth and Kolb, 2012).…”

Section: Avoiding Measurement Biasmentioning

confidence: 99%

Comparative Research Methods

Esser

Vliegenthart²

2017

The International Encyclopedia of Communication Research Methods

142

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In this entry, we discuss the opportunities and challenges of comparative research. We outline the major obstacles in terms of building a comparative theoretical framework, collecting good‐quality data and analyzing those data, and we also explicate the advantages and research questions that can be addressed when taking a comparative approach. Additionally, the entry discusses statistical techniques that can be used to analyze quantitative comparative data, and we end with a discussion on how globalization impacts comparative (mainly cross‐national) research, as well as how such trends might call for the integration of research with multiple research units at multiple levels.

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Measurement invariance in comparative Internet use research

Cited by 6 publications

References 51 publications

Social Environmental Factors and Personal Motivational Factors Associated with Creative Achievement: A Cross‐Cultural Perspective

Social Environmental Factors and Personal Motivational Factors Associated with Creative Achievement: A Cross‐Cultural Perspective

Measuring internet skills in a general population: A large-scale validation of the short Internet Skills Scale in Slovenia

Comparative Research Methods

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