Analysis And Discussion Results Of Rosebery Self-Esteem Scale

Descriptive Statistics

This part will comprise of the analysis results and the discussion of the results from the primary data collected for the Rosebery Self-Esteem Scale (RSES) in the measurement of self-esteem.

This is the analysis that group similar cases to form dimensions. Descriptive statistics for the means of the 10 items were as in the below table;

The variable means was achieved by reducing the number of ten items to one by computing the means of the variables of those who felt they were worthy people and at least on equal plane with others (rse1), those with the feelings that they had a number of good qualities (rse2), those with the general feelings of being failures (rse3), those with the feelings that they can do most of the things other people do (rse4) up to (rse10) those with the feelings that at times they are not good at all. The minimum achieved mean was 1.90 and the maximum of 9.00. The general mean for all the ten items was 5.2665 and the standard deviation of 0.8613. The data values were slightly skewed to the right as shown with skewness of (0.228).

The KMO and Bartlett’s test of sphericity was conducted to check for the analysis to be carried out. As a result, the test significance was greater than the minimum 0.06 i.e. (0.910) which was a superb value for go ahead to use factor analysis. The analysis that was used in the extraction of factors was the principal components analysis. In conjunction with oblimin rotation, Eigen values were used to determine the number of factors from the 10 items.

The communalities table above show the representation of variables with the factors. Almost all the variables were well represented in the common factor space since they had values (greater than 0.5) as in the extraction column. This means the all the items were well represented and suitably used in the research instrument and need not to be removed.

From fifteen variables used, there were 10 components with only two factors retained as in the first two variables shown in the extraction sums of squared loadings in the above table. From the total column, the first factor has the highest Eigenvalue since it accounts for the most variance then followed by the second factor and the trend continues reducing until the least variance accounted for by the last component (component 10) in this case. 58.61% of the variance are accounted by the first factor, 15.995% by second component, and 1.81% by the third component and so on in the decreasing sequence.

Communalities

The scree plot was plotted for Eigenvalue against components from (RSES) test where from the first component to the third component there was great change in the shape of the graph and the graph seems to flatten after the third component showing the least variance accounted for by the remaining components.

For the nomological network of RSES, the Cronbach’s alpha was used to test for the reliability of the ten items used in the online questionnaire. There was internal inconsistency since the Cronbach’s alpha (0.448) was lower than the considered minimum (0.7) hence not fully reliable as from the test.

Reliability of the instrument used was as well tested for the big five factors where general Cronbach’s alpha of 0.144 was achieved which further confirmed that the online instrument was not reliable for use in collection of data.

The item statistics table standard deviation column show that standard deviation values are not uniformly close to one another which further confirms that the used instrument was not reliable and had internal inconsistency.

Referring to the dimensionality, results from this report seem consistent with those in other previous researches including those where RSES was tested and validated Li, Delvecchio, Di Riso, Salcuni & Mazzeschi, (2015); Schaefer et al (2015). This is also in line with British and China studies about Rosenberg Self-Esteem Scale and use of big five index to measure self-esteem (Sariyska et al., 2014; Dufner et al., 2012).In the analysis full extraction of the correlation of factors in relation to Rosenberg Self-Esteem Scale (RSES) factor analysis, the data was found to be partially skewed to the right hand side as it was reflected by the skewness value (0.228). The item wording effect made RSES a two dimension otherwise it was believed to be a one dimension (Kong, Zhao & You, 2012). The psychometric evaluation of personality scale from the factor analysis through principal component extracted two major factors where most of the variance were accounted for. The choice of factor analysis was ended up with from the KMO value (0.91) which was most suitable for the analysis to be conducted. All the items in the Likert scale belonged to their respective scales as the extraction values were all greater than (0.5). The Cronbach’s alpha from the reliability test of the instrument used was less than 0.5 i.e. (0.448). This showed that the instrument had lower internal consistency thus could not be relied on. The big five factors’ standard deviation also confirmed that the instrument was not reliable since the standard deviation values were not too close or onto one another.

From the results in the factor analysis, it is not quite easy to decide on the number of factors to be included and used in the process. Further, the factors that were used could be difficult to assume that they represent the data. The ten point scale in the data was not suitable as the Rosenberg Self-Esteem Scale is best for four scale in the ten items. In the future therefore, the appropriate scale should be considered and the ten items.

Conclusion

The construct validity and reliability test of the online instrument used was tested using the Cronbach’s alpha. The principal component was used in the extraction of factors out of which two factors were resulted with. RSES was found to be one of the suitable measure of self-esteem since it is easy to understand. The big five framework i.e. openness, conscientiousness, extraversion agreeableness and neuroticism were in this report included in the test of internal consistency which agreed with the RSES ten items five point Likert scale. 

References

Dufner, M., Denissen, J. J., Zalk, M., Matthes, B., Meeus, W. H., van Aken, M. A., & Sedikides, C. (2012). Positive intelligence illusions: On the relation between intellectual self?enhancement and psychological adjustment. Journal of Personality, 80(3), 537-572.

Kong, F., Zhao, J., & You, X. (2012). Emotional intelligence and life satisfaction in Chinese university students: The mediating role of self-esteem and social support. Personality and Individual Differences, 53(8), 1039-1043.

Li, J. B., Delvecchio, E., Di Riso, D., Salcuni, S., & Mazzeschi, C. (2015). Self-esteem and its association with depression among Chinese, Italian, and Costa Rican adolescents: A cross-cultural study. Personality and Individual Differences, 82, 20-25.

Sariyska, R., Reuter, M., Bey, K., Sha, P., Li, M., Chen, Y. F., … & Feldmann, M. (2014). Self-esteem, personality and Internet addiction: a cross-cultural comparison study. Personality and Individual Differences, 61, 28-33.

Schaefer, L. M., Burke, N. L., Thompson, J. K., Dedrick, R. F., Heinberg, L. J., Calogero, R. M., … & Anderson, D. A. (2015). Development and validation of the Sociocultural Attitudes Towards Appearance Questionnaire-4 (SATAQ-4). Psychological Assessment, 27(1), 54.

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