この節の作者: Rebecca Vederhus, Sebastian Jentschke

From SPSS to jamovi: Analysis of frequencies

This comparison shows how a Chi-square test is conducted in SPSS and jamovi. The SPSS test follows the description in chapters 19.7.2-19.7.3 in Field (2017), especially figures 19.4-19.5 and output 19.2-19.4. It uses the data set Cats Weight.sav which can be downloaded from the web page accompanying the book.

SPSS

jamovi

In SPSS, you run a chi-square test using : AnalyzeDescriptive StatisticsCrosstabs. Before this, you can weight cases by following these steps: DataWeight Cases.

In jamovi, this can be done using: AnalysesFrequenciesIndependent Samples χ² test of association.

SPSS_Menu_chi-square_1

jamovi_Menu_chi-square

SPSS_Menu_chi-square_2

In the Weight Cases window, click Weight cases by and move Frequency to the box called Frequency Variable.

In jamovi, move Training to Rows, Dance to Columns, and Frequency to Counts (optional).

SPSS_Input_chi-square_1

jamovi_Input_chi-square_1

In SPSS, move the Training variable to the Row(s) box and the Dance variable to the variable box Column(s).

Open the Statistics window and tick the boxes for: χ², continuity correction, Likelihood ratio, Fisher’s exact test, Confidence intervals, Contingency coefficient and Phi and Cramer’s V.

SPSS_Input_chi-square_2

jamovi_Input_chi-square_2

Open the Statistics window and check the boxes for Chi-square, Contingency coefficient, Phi and Cramer’s V and Lambda.

In the window for Cells, tick all the boxes.

SPSS_Input_chi-square_3

jamovi_Input_chi-square_3

Access Cells from the main menu, and tick the boxes as shown in the picture below.

SPSS_Input_chi-square_4

Lastly, open the window for Exact and click Exact and Time limit per test: 5 minutes.

SPSS_Input_chi-square_5

When comparing the output from SPSS and jamovi, the results are exactly the same, although in jamovi they are much clearer and therefore easier to interpret.

SPSS_Output_chi-square_1

jamovi_Output_chi-square

SPSS_Output_chi-square_2

SPSS_Output_chi-square_3

In SPSS, the Crosstabulation table shows the amount of cases that can be categorized into each combination. We can see the amount of cats that danced, and how many of these were rewarded with food or affection. In the Chi-Square Tests table, you can find the statistic of the chi-square and the significance level of this value. Degrees of freedom are also presented in this table. The measures of association is presented in the Symmetric Measures table. By looking at these values, you can find an estimate of the effect size.

The contingency table in jamovi contains all the same values as in SPSS, except for Standardized Residual. In jamovi, the chi-square tests are presented in the table called χ² Tests. In contrast to SPSS, this table does not include columns for Exact Sig. (2-sided), Exact Sig. (1-sided) and Point Probability, or a row for Linear-by-Linear Association. You can find the measures of association in the Nominal table. Values for Approximate Significance and Exact Significance are not included in jamovi.

The only difference between the outputs in SPSS and jamovi is that SPSS produces Case Processing Summary and Directional Measures tables.

The numerical values for the statistics are the same: χ² (1, N = 200) = 25.36, p < .001.

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.

WEIGHT BY Frequency.
CROSSTABS
  /TABLES=Training BY Dance
  /FORMAT=AVALUE TABLES
  /STATISTICS=CHISQ CC PHI LAMBDA
  /CELLS=COUNT EXPECTED ROW COLUMN TOTAL SRESID BPROP
  /COUNT ROUND CELL
  /METHOD=EXACT TIMER(5).
jmv::contTables(
    formula = Frequency ~ Training:Dance,
    data = data,
    chiSqCorr = TRUE,
    likeRat = TRUE,
    fisher = TRUE,
    contCoef = TRUE,
    phiCra = TRUE,
    exp = TRUE,
    pcRow = TRUE,
    pcCol = TRUE,
    pcTot = 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