I have collected data using questionnaires from athletes at two time points. I have an independent variable (leadership) and a few dependent variables but also some mediating or indirect variables such as trust ect. All of the variables were measured using the same questionnaire at two time points.
What data analysis method would be best to analyse the data? So far I have used the Process macro on SPSS which uses OLS regressions but I am unsure if this is the best method.
I essentially want to see how the IV relates/ increases the dependant variables over time and whether this changed occurred directly from the IV and indirectly through the mediators. Would these be appropriate research questions for the type of data I have and for the appropriate analysis technique?
Hello Ela,
a) learn SEM--for instance with the lavaan-package (lavaan.org)
b) For your research question, autoregressive models would be a possibility in which you can model lagged or synchronous direct and indirect effects.
Here is an applied example. If this fits what you want, I'll give you further papers.
Frese, M., Garst, H., & Fay, D. (2007). Making things happen: Reciprocal relationships between work characteristics and personal initiative in a four-wave longitudinal structural equation model. Journal of Applied Psychology, 92(4), 1084-1102.
(don't be distracted that they used 4 waves)
Best,
Holger
According to my knowledge, you can use independent samples t-test to find out the difference between the of the baseline socre and final score.
However, I refer you to focus on Holger Steinmetz's suggestion
You may use Structure Equation modelling, name the variables as T1 or T2 and do the analysis as in this publication: A Time-lagged Analysis of the Effect of Authentic Leadership on Workplace Bullying, Burnout and Occupational Turnover Intentions
10.1080/1359432X.2013.804646 .
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