- #1
thelema418
- 132
- 4
I need to create scales for a test before running t-tests / ANOVA.
Instrument: One attitude survey test with 37 questions. Each question is a Likert type question with 1 to 5 points.
Data Set: The set of data includes pre-test and post-test scores. There was a 6 month delay between the pre-test and post-test.
The question is this -- my original tables have rows of participants and columns for Pre-scores and Post-scores. Some people have told me to run FA on the difference between Pre-Scores and Post-Scores. (This reduces the sample size because some people skipped questions or did not take the post-test). The KMO becomes less than .300 because of this.
Another idea is to treat the participants as different in terms of time, so that there is a Pre-Participant and Post-Participant in the rows. The columns will only be questions. This way we can create factor scores and then merge these scores as pre- and post-scores. When the data is handled this way, the KMO is greater than .700. But some have issued concerns about "replicating" individuals when doing this.
In the statistical literature, I haven't seen anything written about either issue with data for FA in terms of making scales. Any insight would be appreciated. Thanks.
Instrument: One attitude survey test with 37 questions. Each question is a Likert type question with 1 to 5 points.
Data Set: The set of data includes pre-test and post-test scores. There was a 6 month delay between the pre-test and post-test.
The question is this -- my original tables have rows of participants and columns for Pre-scores and Post-scores. Some people have told me to run FA on the difference between Pre-Scores and Post-Scores. (This reduces the sample size because some people skipped questions or did not take the post-test). The KMO becomes less than .300 because of this.
Another idea is to treat the participants as different in terms of time, so that there is a Pre-Participant and Post-Participant in the rows. The columns will only be questions. This way we can create factor scores and then merge these scores as pre- and post-scores. When the data is handled this way, the KMO is greater than .700. But some have issued concerns about "replicating" individuals when doing this.
In the statistical literature, I haven't seen anything written about either issue with data for FA in terms of making scales. Any insight would be appreciated. Thanks.