What are the scales for measurement of the items of the measures?
According to (Louangrath & Sutanapong, 2018), the scale used in this study lacks zero value which is a significant problem when analyzing data. Therefore this suggests that the scale used here is the ordinal scale of measure that combines both nominal and ordinal scale characteristics. In these scales, zero is not applicable. It only places data about the behavioral concerns of the teenage girls in a specific order without information that differentiate them.
Are there any reverse-scored items that need to be restored before data can be analyzed?
There are no reverse-scored items in the research conducted since the items under the measure with high scores do not indicate the opposite of the behavior concerns being evaluated.
Are there subscales or total scales that need to be calculated?
The subscales that need to be calculated include the attachment to school, friends, and teachers. Primarily, these are the sub-dimension in the behavioral concerns of the teenage (Alan & Kabasakal, 2020).
How can the variables in the database be labeled to identify the correct items best and avoid future errors?
A database needs to be created characterized by driven label templates to identify correct items and avoid future errors. The variable fields will be created within the database, and the print user is used to identify correct items. Data validation in the labeling process is essential for avoiding future errors. Also, setting the label templates is vital as the invalidated variable data will not be printed. Notably, in future, if an error occurs, it can be resolved by tracing the steps involved in labeling where a person and the time when an incorrect label occurred.
How can errors in the data entry be identified or caught to ensure valid results?
Detecting errors in the data entry for validity always involves checking each variable used in the research for the scores entered out of the relevant range. In this case, each variable is inspected to identify if it falls within the relevant range. The case in which data error is involved is then identified, the value corrected or deleted if not necessary.
References
Alan, Ü., & Kabasakal, K. A. (2020). Effect of the number of response options on the psychometric properties of Likert-type scales used with children. Studies in Education
Jebb, A. T., Ng, V., & Tay, L. (2021). A review of critical Likert scale development advances 1995–2019—frontiers in psychology, 12, 1590.
Louangrath, P. I., & Sutanapong, C. (2018). Validity and reliability of survey scales. International Journal of Research & Methodology in Social Science, 4(3), 99-114.
These are the question need to question again but using CABI Instrument information