Section author: Rebecca Vederhus, Sebastian Jentschke

From SPSS to jamovi: Correlation

This comparison shows how a semi-partial (or partial) correlation is conducted in SPSS and jamovi. The SPSS test follows the description in chapter 8.5.3 in Field (2017), especially figure 8.11 and output 8.5. It uses the data set Exam Anxiety.sav which can be downloaded from the web page accompanying the book.

SPSS

jamovi

In SPSS you can run a partial correlation using: Analyze → Correlate → Partial.

In jamovi you do this using: Analyses → Regression → Partial Correlation.

SPSS_Menu_corr5

jamovi_Menu_corr5

In SPSS, move the variables Exam `` and ``Anxiety to the variable box Variables, and Revise into the box called Controlling for.

In jamovi, move the variables Exam and Anxiety into the Variables box and Revise into the variable box Control Variables. Tick Pearson under Correlation Coefficients``and ``Report significance under Additional Options.

SPSS_Input_corr5

jamovi_Input_corr5

The results are the same in SPSS and in jamovi.

SPSS_Output_corr5_1

jamovi_Output_corr5

SPSS_Output_corr5_2

In SPSS, you can tell if a correlation is significant by noting the amount of asterisks after the correlation coefficient. The correlation matrix shows the correlation coefficient, the p-value, and the sample size (N).

In jamovi, significant correlations are flagged using one (p < .05), two (p < .01) or three (p < .001) asterisks. This differs from SPSS, where all correlation above p < .01 level is simply marked using two instead of three asterisks.

Results are presented twice in SPSS, while in jamovi they are only presented once. The numerical values for the statistics are identical: r = -.25.

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.

 
PARTIAL CORR
  /VARIABLES=Exam Anxiety BY Revise
  /SIGNIFICANCE=TWOTAIL
  /MISSING=LISTWISE.

jmv::corrPart(
    data = data,
    vars = vars(Exam, Anxiety),
    controls = Revise)

SPSS output file containing the analyses

jamovi file containing the analyses
References
Field, A. (2017). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications. https://edge.sagepub.com/field5e