Section author: Rebecca Vederhus, Sebastian Jentschke

From SPSS to jamovi: Correlation

This comparison shows how a Spearman’s correlation is conducted in SPSS and jamovi. The SPSS test follows the description in chapter 8.4.3 in Field (2017), especially output 8.2. It uses the data set The Biggest Liar.sav which can be downloaded from the web page accompanying the book.

SPSS

jamovi

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

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

SPSS_Menu_corr2

jamovi_Menu_corr2

In SPSS, move the variables Creativity and Position to the variable box Variables. In addition, tick the box called Spearman under Correlation Coefficients.

In jamovi, move the variables Creativity and Position into the box on the right. Tick Spearman under Correlation Coefficients and Report significance, Flag significant correlations and N under Additional Options.

SPSS_Input_corr2

jamovi_Input_corr2

The results in SPSS and in jamovi are the same.

SPSS_Output_corr2

jamovi_Output_corr2

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).

jamovi, in accordance with APA-style, flags significant correlations using one (p < .05), two (p < .01) or three (p < .001) asterisks. In contrast, in SPSS all correlations above p < .01 level are simply marked using two instead of three asterisks.

As in analysis on the previous page, the correlation coefficient is found both underneath and over the diagonal in SPSS, while in jamovi the coefficient is only shown underneath. The numerical values for the statistics are identical: r = -0.37, p < .01.

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.

 
NONPAR CORR
  /VARIABLES=Creativity Position
  /PRINT=SPEARMAN TWOTAIL NOSIG FULL
  /MISSING=PAIRWISE.

jmv::corrMatrix(
    data = data,
    vars = vars(Creativity, Position),
    pearson = FALSE,
    spearman = TRUE,
    flag = TRUE,
    n = TRUE)

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