Suchergebnisse

The construct of justice sensitivity has four perspectives that capture individual differences in the strength of reactions to injustice when becoming a victim of injustice (victim sensitivity), when witnessing injustice as an outsider (observer sensitivity), when passively benefitting from an injustice done to others (beneficiary sensitivity), or when committing an injustice (perpetrator sensitivity). Individual differences in these four justice sensitivity perspectives are highly relevant in moral research. With just eight items in total, the Justice Sensitivity Short Scales–8 (JSS-8) are a very efficient way to measure the four perspectives. JSS-8 was initially constructed in German (Ungerechtigkeitssensibilität-Skalen-8, USS-8) and later translated into English. In the present study, we empirically validated this English-language adaptation in a heterogeneous quota sample from the UK. The results show that the psychometric properties (i.e., reliability, validity, standardization) of JSS-8 are good, and that they are comparable with those of the German-language source version. Because of the invariance of loadings, intercepts, and residual variances, researchers can compare manifest scale statistics (i.e., means, variances) of JSS-8 across the UK and Germany. JSS-8 is thus particularly suitable for measuring justice sensitivity in various research areas with constraints on assessment time and questionnaire space. - Data Availability Statement: The data that underly the results of this study are openly available in GESIS SowiDataNet - datorium repository (https://doi.org/10.7802/2096).

Here you find Mplus code, which is used for the development and validation of measurement instruments (questionnaire, test, items, scale) for the social sciences. The description of the analyses carried out with the code can be found in the appendices A1 to A5 of the ZIS Publication Guide. Each code includes comments to guide users through the code. We provide the data set "example1" to run the code.



We provide:

Code for testing the dimensionality of scales comprises exploratory factor analysis, exploratory structural equation modeling (SEM), and confirmatory factor analysis (tau-congeneric and tau-equivalent). For the description of the analyses, see appendices A1 to A2 of the ZIS Publication Guide.


Code used to estimate reliability comprises the estimation of split-half reliability, retest reliability, reliability coefficients for single-factor models (Cronbach's Alpha, McDonald's Omega/Raykov's Rho, AVE [Average Variance Extracted]), and bi-factor models (Omega-H, ECV [Explained Common Variance]). For the description of the analyses, see appendix A3 of the ZIS Publication Guide.


Code for measurement invariance testing within SEM. For the description of the analyses see appendix A5 of the ZIS Publication Guide.

Here you find R code, which is used for the development and validation of measurement instruments (questionnaires, tests, items, scales) for the social sciences. The description of the analyses carried out with the codes can be found in the appendices A1 to A5 of the ZIS Publication Guide. Each code includes comments to guide users through the code. We provide the data set "example1" to run the code.



We provide:

Code for testing the dimensionality of scales comprises exploratory factor analysis, principal component analysis, and confirmatory factor analysis (tau-congeneric and tau-equivalent). For the description of the analyses, see appendices A1 to A2 of the ZIS Publication Guide.


Code used to estimate reliability comprises the estimation of split-half reliability, retest reliability, reliability coefficients for single-factor models (Cronbach's Alpha, McDonald's Omega/Raykov's Rho, AVE [Average Variance Extracted]), and bi-factor models (Omega-H, ECV [Explained Common Variance]). For the description of the analyses, see appendix A3 of the ZIS Publication Guide.

Code for measurement invariance testing within SEM. For the description of the analyses see appendix A5 of the ZIS Publication Guide.

Here you find Stata code, which is used for the development and validation of measurement instruments (questionnaires, tests, items, scales) for the social sciences. The description of the analyses carried out with the code can be found in the appendices A1 to A5 of the ZIS Publication Guide. Each code includes comments to guide users through the code. We provide the data set "example1" to run the code.


We provide:

Code for testing the dimensionality of scales comprises exploratory factor analysis, principal component analysis, and confirmatory factor analysis (tau-congeneric and tau-equivalent). For the description of the analyses, see appendices A1 to A2 of the ZIS Publication Guide.

Code used to estimate reliability comprises the estimation of split-half reliability, retest reliability, reliability coefficients for single-factor models (Cronbach's Alpha, McDonald's Omega/Raykov's Rho, AVE [Average Variance Extracted]), and bi-factor models (Omega-H, ECV [Explained Common Variance]). For the description of the analyses, see appendix A3 of the ZIS Publication Guide.

Code for measurement invariance testing within SEM. For the description of the analyses see appendix A5 of the ZIS Publication Guide.