The data used in Chapter 14, Table 3
An object of class
data.frame with 10 rows and 3 columns.
Using the data in Table 14.1, we could average scores for each participant individually because the noise factor we need to average over is a within-subjects factor. For example, participant 1's average 0 degree score is 450, whereas his or her 8 degree score is 630. This participant's reaction time averages 180 msec longer (630 vs 450) for the 8 degree condition than the 0 degree condition. If the other 9 participants' data show a similar pattern, we would infer that there is indeed a main effect due to angle.
For the hypothetical data contained in Table 14.1, Table 14.3 gives the set of D variables. The D variables are subsequently used to analyze the data given in Table 14.1. Recall that we analyzed the data contained in Table 14.1 directly using SPSS without (explicitly) forming D variables. Although obtaining the results of the main effects is easily accomplished using the data directly, forming and then analyzing D variables directly also has its benefits (which are delineated in the chapter). Below we analyze the D variables contained in Table 14.3. As expected, our results will match those previously obtained when we analyzed the raw data (i.e., skipping the step of explicitly forming D variables). However, the method to be outlined here provides a different way to accomplish the same goal. We will soon see that analyzing the data by explicitly forming D variables has its advantages.The first column of Table 14.3 (D1) shows these scores for all 10 participants. Indeed, all 10 participants have an average 8 degree reaction time that is slower than their average 0 degree reaction time. Such consistency strongly supports the existence of an angle main effect.
participant D1 difference score averaged over noise
participant D2 difference score averaged over noise
participant D3 difference score averaged over noise
Ken Kelley [email protected]
Maxwell, S. E., Delaney, H. D., \& Kelley, K. (forthcoming). Designing experiments and analyzing data: A model comparison perspective. (3rd ed.). Routledge.
Maxwell, S. E., Delaney, H. D., \& Kelley, K. (forthcoming). Designing experiments and analyzing data: A model comparison perspective (3rd ed.). Routledge.
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