この節の作者: Sebastian Jentschke
From SPSS to jamovi: ttest for paired samples¶
After having demonstrated the beneficial effect of repeatedmeasuresdesigns on the standard error of mean, we conduct a ttest for paired samples. Using this test, we compare whether the number of mischieveous acts has increased after receiving a cloak of invisibility (variable
Cloak
) in comparison to the number of mischieveous acts at baseline (variableNo_Cloak
). This analysis is described in chapter 10.9.3 of Field (2017), especially Figure 10.12 and Output 10.8  10.9. We use the same data set Invisibility RM.sav which can be downloaded from the web page accompanying Andy Field's book.
SPSS 
jamovi 

In SPSS you can set up a ttest for paired samples using: 
In jamovi you do this using: 
In the input window that opens, the two variables 
In the input panel that opens, the variables 
Afterwards, we press the 
In jamovi, do we go further down in the input panel and tick 
The results from SPSS and jamovi are identical, but they are arranged slightly differently. SPSS gives the mean difference (blue box) first, before giving
the tstatistics and their respective degrees of freedom and pvalue (red box), in jamovi it is the other way round (statistics – red box – first and mean
difference – blue box – afterwards). Another table underneath (green box) gives the descriptive statistics for the two variables that were compared. Except
from that jamovi also reports the Median, and a slightly different way to arrange the columns (SPSS begins with the 

SPSS, in addition, gives the 

If you wish to replicate those analyses using syntax, you can use the commands below (in jamovi, just copy to code below to Rj). Alternatively, you can download the SPSS output files and the jamovi files with the analyses from below the syntax. 

TTEST PAIRS=No_Cloak WITH Cloak (PAIRED)
/CRITERIA=CI(.95)
/MISSING=ANALYSIS.

jmv::ttestPS(
data = data,
pairs = list(
list(
i1="No_Cloak",
i2="Cloak")),
meanDiff = TRUE,
ci = TRUE,
desc = TRUE)
