Psychology has become less WEIRD in recent years, marking progress toward becoming a truly global psychology. However, this increase in cultural diversity is not matched by greater attention to ...cultural biases in research. A significant challenge in culture-comparative research in psychology is that any comparisons are open to possible item bias and non-invariance. Unfortunately, many psychologists are not aware of problems and their implications, and do not know how to best test for invariance in their data. We provide a general introduction to invariance testing and a tutorial of three major classes of techniques that can be easily implemented in the free software and statistical language R. Specifically, we describe (1) confirmatory and multi-group confirmatory factor analysis, with extension to exploratory structural equation modeling, and multi-group alignment; (2) iterative hybrid logistic regression as well as (3) exploratory factor analysis and principal component analysis with Procrustes rotation. We pay specific attention to effect size measures of item biases and differential item function. Code in R is provided in the main text and online (see https://osf.io/agr5e/), and more extended code and a general introduction to R are available in the Supplementary Materials.
•Confirmatory composite analysis (CCA) can confirm measurement models using PLS-SEM.•CCA has benefits relative to confirmatory factor analysis (CFA).•CCA can confirm both reflective and formative ...measurement models.•Guidelines for the proper application of CCA are provided.•PLSpredict procedure for out-of-sample prediction with CCA is explained.•CCA also does not require fit to confirm measurement models.
Confirmatory factor analysis (CFA) has historically been used to develop and improve reflectively measured constructs based on the domain sampling model. Compared to CFA, confirmatory composite analysis (CCA) is a recently proposed alternative approach applied to confirm measurement models when using partial least squares structural equation modeling (PLS-SEM). CCA is a series of steps executed with PLS-SEM to confirm both reflective and formative measurement models of established measures that are being updated or adapted to a different context. CCA is also useful for developing new measures. Finally, CCA offers several advantages over other approaches for confirming measurement models consisting of linear composites.
This article presents a configuration that can simulate both a resistor in
series with a frequency-dependent negative-resistance (R-D) and a resistor
in series with a capacitor (R-C), with a ...different selection of passive
elements. The proposed circuit employs only two
current-controlled-current-feedback- amplifiers (CC-CFAs) and grounded
passive elements. This configuration does not require passive element
matching, and the simulated equivalent element values can be tuned
electronically by applying a biasing current to the CC-CFAs. To demonstrate
the application of the proposed grounded series R-D impedance simulator, it
is applied to a second-order notch filter and a fifth-order elliptic lowpass
filter, whereas the series R-C impedance simulator is applied to a
secondorder resonance circuit to find the band-pass response of the input
current. Our theoretical analysis is confirmed by the results of a PSPICE
simulation.
Within the distance education community, the Community of Inquiry (COI) framework is widely accepted as a framework to understand and design text-based learning environments. The framework includes ...three components: Cognitive Presence, Teaching Presence, and Social Presence. Recent work has proposed the addition of a fourth component, Learning Presence, which reflects students' self-regulation, and its role within the original framework. This study evaluated alternative structures of the COI framework to explain student perceptions of learning online. The study participants (n = 256) were graduate students from multiple institutions who had taken at least one fully online course as part of their degree requirements. Survey data were collected using a single Likert-scaled survey instrument. Presented herein are the results of the first phase of a two-part study, which included a series of confirmatory factor analyses to evaluate the measurement models of the four COI constructs individually, followed by a model including all four constructs simultaneously. Future work on the second phase of the this two-part study evaluated a series of structural models using path analyses and hierarchical linear regression analyses. Findings indicated that teaching presence reached a more parimonious model with two subscales as opposed to the three subscales of the COI survey. A new subscale "peer faciliation" was proposed for teaching presence, but had better model fit as a subscale of social presence. The three existing subscales of social presence could also more parsimoniously represented with two subscales, with the new "peer faciliation" subscale acting as the third. Finally, learning presence was modeled with three subscales, and was the strongest overall predictor of cognitive presence, compared to teaching and social presence. This work makes unique contributions to the study of online learning environments through the COI framework by introducing a comprehensive survey that includes Learning Presence indicators, producing evidence on the multi-dimensionality of the COI constructs, and the strong relationship between Learning Presence and Cognitive Presence.
•Analysis and discussion of the COI framework with student self-regulation represented as learning presence•Modeling and testing COI factor dimensionality with hierarchical second-order CFA•Modified survey instrument that includes the measurement of learning presence with indicators of self-regulatory charateristics
Many constructs in management studies, such as perceptions, personalities, attitudes, and behavioral intentions, are not directly observable. Typically, empirical studies measure such constructs ...using established scales with multiple indicators. When the scales are used in a different population, the items are translated into other languages or revised to adapt to other populations, it is essential for researchers to report the quality of measurement scales before using them to test hypotheses. Researchers commonly report the quality of these measurement scales based on Cronbach’s alpha and confirmatory factor analysis results. However, these results are usually inadequate and sometimes inappropriate. Moreover, researchers rarely consider sampling errors for these psychometric quality measures. In this best practice paper, we first critically review the most frequently-used approaches in empirical studies to evaluate the quality of measurement scales when using structural equation modeling. Next, we recommend best practices in assessing reliability, convergent and discriminant validity based on multiple criteria and taking sampling errors into consideration. Then, we illustrate with numerical examples the application of a specifically-developed R package, measureQ, that provides a one-stop solution for implementing the recommended best practices and a template for reporting the results. measureQ is easy to implement, even for those new to R. Our overall aim is to provide a best-practice reference for future authors, reviewers, and editors in reporting and reviewing the quality of measurement scales in empirical management studies.
Urban agriculture or better known as urban farming is the practice of cultivating, processing, and distributing food around the city. Urban agriculture can also involve animal husbandry, aquaculture, ...agroforestry, and horticulture. Banjarbaru City as the capital of South Kalimantan Province which is also the center of government of South Kalimantan Province since 2022, its status as the capital of South Kalimantan province has been determined, replacing Banjarmasin City. As an urban area, the city of Banjarbaru has limited land mainly for agricultural purposes. To answer these problems, the city of Banjarbaru introduced the concept of Urban Farming in one of the Food Security programs of the city of Banjarbaru. Based on the formulation of the study, as stated above, the objectives of this study are as follows; 1) Identifying potentials and problems in Banjarbaru City for the development plan of Urban Farming activities from a social aspect; 2) Identify community preferences for the Urban Farming Program in Banjarbaru City. The sampling method in this study was simple random sampling, with the number of samples taken as many as 100 people. The data analysis used in this study is descriptive analysis and Confirmatory Factor Analysis (CFA). Based on the results of the study shows that the 5 main factors that support the greatest urban farming potential in Banjarbaru City include; 1) the factor of land that is still available by 17%; 2) factor into additional income of 14%; 3) government support factor of 13%; 4) factor reduces food expenditure by 12%; and 5) the factor of local food demand of 11%. While the dominant actors formed for each community's preferences in urban farming, can be seen from the variables that have the highest loading factor value. In the aspect of the purpose of implementing urban farming, the dominant factor formed is education with a loading factor value of 0.875. In the urban farming type technique, the direct yard land factor with a loading factor value of 0.869, while the type of crop / commodity for urban farming is a farm with a loading factor value of 0.747.
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