Thank you for allowing me to join this community!
I want to conduct a small TSSEM using individual participant data from six studies. Since I have the raw data for each study, I am running into a problem with multiple measures of single constructs. Essentially, I have many relationships, but I don’t have many studies. Here is a simplified example of four constructs in one study, using different measures:
Predictor1 – Measure A
Predictor1 – Measure B
Predictor2 – Measure A
Predictor2 – Measure B
Predictor2 – Measure C
Outcome1 – Measure A
Outcome1 – Measure B
Outcome1 – Measure C
Outcome2 – Measure A
In order to get my pooled correlations for TSSEM Step One, I need to obtain effect sizes for each study relationship. In the example above, I have six Predictor1-Outcome1 effect sizes but I need a single Predictor1-Outcome1 effect sizes in order to pool my data across studies.
From what I understand in Cheung’s (2015, p. 181) textbook is that I need to average these effect sizes. Since I have so few studies, I am hoping there is an alternative to this? Each study contains alternative measures of the same construct so I feel like I am losing a lot of information by potentially averaging them together.
Thank you for reading this! I appreciate any guidance, additional readings, or suggested search terms! Thank you!
Nicole
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Hi Nicole,
TSSEM is a special case of general SEM without the raw data. If you have the raw data, you should frame it under the appropriate SEM models, e.g., the multiple-group SEM. It is always easier to do it in general SEM than in the TSSEM.
Mike