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* [:FAQ/singcase/abnorm: Confidence Intervals for Abnormality] |
Comparing a within subjects group difference to that of a single case
Pairwise case
Suppose a group of controls and a single case do a pair of conditions (c1, c2, say) and we are interested in seeing if the relationship between the conditions in the controls is the same as that in the single case.
Since we have a single case we can treat its difference as a constant. So we end up with a one sample t-test on the control group difference minus the case difference. Ie we test if the mean difference in controls - difference in case equals 0.
There is a one-sample t-test option under analyze:means in SPSS. The two-sample (independent samples) may also be performed on the difference in SPSS. Alternatively the below example will work using R. Here c1 and c2 are the two conditions and sub denotes if the subject is a control or a case.
Note that these tests assume that the slopes in the control and patient groups have the same variance. [attachment:crawford.pdf A detailed discussion of the methods is available.]
c1 <- c(2,1,2,3,1,2,2,1,1,3,3,1) c2 <- c(3,4,1,1,6,1,3,2,2,5,2,2) sub <- c(1,1,1,1,1,1,1,1,1,1,1,2) diff <- c1–c2 diffn <- diff[sub == 1] diffp <- diff[sub == 2] diffy <- diffn - diffp const <- gl(1,length(diffn)) id <- gl(length(diffn),1) t.test(diffy, mu=0) df <- length(diffn)-1 toutc <- (mean(diffn)-diffp) / sqrt(var(diffn)*((nc+1)/nc)) pv <- 2*pt(-abs(toutc), df)
- [:FAQ/singcase/multiW: Three or more conditions]
- [:FAQ/singcase/abnorm: Confidence Intervals for Abnormality]