この節の作者: Rebecca Vederhus, Sebastian Jentschke
From SPSS to jamovi: Analysis of Covariance (ANCOVA)¶
This comparison shows how to conduct an analysis of covariance in SPSS and jamovi. The SPSS test follows the description in chapter 13.5.4 - 13.5.6 in Field (2017), especially figure 13.5 - 13.7 (excludingOptions
) and outputs 13.6 - 13.11 (excludingBootstrap
, as this is not [yet] an option in jamovi). It uses the data set Puppy Love.sav which can be downloaded from the web page accompanying the book.
SPSS | jamovi |
---|---|
In SPSS, you can run this test using: Analyze → General Linear Model
→ Univariate . |
In jamovi you do this using: Analyses → ANOVA → ANCOVA . |
In SPSS, move Happiness to the Dependent Variable box, Dose to
the Fixed Factor(s) box, and Puppy_love into Covariate(s) . |
In jamovi, move Happiness to the Dependent Variable box, Dose to
the Fixed Factors box and Puppy_love into Covariates . |
Then, open the dialog box called Contrasts , and click the drop-down menu
to select Simple . Change the Reference Category to First , and
press Change . |
Open the Contrasts window, and select simple from the drop-down menu. |
Select EM Means from the sidebar. Move Dose to the box called
Display Means for: , press Compare main effects and select Sidak
in the drop-down list. |
Then, move Dose to Term 1 in the Estimated Marginal Means window.
Tick the box for Marginal means tables as shown in the picture below. |
When comparing the output from SPSS and jamovi, the results are the same. However, SPSS provides a lot more, rather unnecessary output than jamovi. These outputs are not included here. | |
In SPSS, you can find the adjusted values of the group means in the
Estimates table. By looking at the Mean you can find out if there
are any changes in happiness levels if there is an increase in puppy
exposure. The Tests of Between-Subjects Effects table shows the sum of
squares for the Dose variable, and this tells us how many units of
variance this factor account for. In the Contrast Results (K Matrix)
table, level 2 (15 mins) is compared with level 1 (control) and then level 3
(30 mins) is compared with level 1 (control). Here, the group differences are
indicated by standard error, a difference value and a p-value. |
In jamovi, the adjusted values can be found in the table called Estimated
Marginal Means – Dose . This table looks exactly the same as the equivalent
table in SPSS. Sum of squares are found in the ANCOVA – Happiness table.
These tables differ slightly in SPSS and in jamovi, as jamovi only gives
results for Dose and Residuals . The contrast analysis in jamovi also
does not provide all of the values that the SPSS analysis does. However, the
most important information is included. |
jamovi does not include the values for the The numerical values for these analyses are the same: SS*<sub>Dose</sub> = 25.19, *p < .05; SS*<sub>Puppy_love</sub> = 15.08, *p < .05; M*<sub>Control</sub> = 2.93, *M*<sub>15mins</sub> = 4.71, *M*<sub>30mins</sub> = 5.15; contrast 1, *p = 0.045; contrast 2, p = 0.010. |
|
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. | |
UNIANOVA Happiness BY Dose WITH Puppy_love
/CONTRAST(Dose)=Simple(1)
/METHOD=SSTYPE(3)
/INTERCEPT=INCLUDE
/EMMEANS=TABLES(Dose) WITH(Puppy_love=MEAN) COMPARE ADJ(SIDAK)
/CRITERIA=ALPHA(0.05)
/DESIGN=Puppy_love Dose.
|
jmv::ancova(
formula = Happiness ~ Dose + Puppy_Love,
data = data,
contrasts = list(list(var = "Dose", type = "simple")),
emMeans = ~ Dose,
emmPlots = FALSE,
emmPlotError = "none",
emmTables = TRUE)
|
SPSS output file containing the analyses | jamovi file containing the analyses |