Chapter 16 Omega
16.1 Intro
Omega is considered a measure of internal consistency and can, if a number of assumptions are met, estimate the reliability of a set of items.
16.2 Input: jamovi
In the “Analyses” tab, click the “Factor” button and from the menu that appear, select “Reliability Analysis” as shown in Figure 16.1.

Figure 16.1: Opening the reliability analysis menu in jamovi
In the box at the left, select all variables you want to include in this analysis and move them to the box labelled “Items” using the button labelled with the rightward-pointing arrow as shown in Figure 16.2.

Figure 16.2: Adding the items to analyse in jamovi
Select the checkbox labelled “Omega” in the left-most column at the bottom labelled “Scale Statistics”, as shown in Figure 16.3.

Figure 16.3: Ordering “Selecting Omega in jamovi
You can now also order additional statistics, such as the value Omega would have if you were to omit each item, as shown in Figure 16.4.

Figure 16.4: Ordering “Omega if item dropped” in jamovi
16.3 Input: R
::reliability(
rosettadata = dat,
items = c(
"highDose_AttGeneral_good",
"highDose_AttGeneral_prettig",
"highDose_AttGeneral_slim",
"highDose_AttGeneral_gezond",
"highDose_AttGeneral_spannend"
) );
16.5 Output: jamovi

Figure 16.5: The output of a reliability analysis where Omega is computed in jamovi
16.6 Output: R
16.6.1 R: rosetta
16.6.1.1 Reliability analysis
16.6.1.1.1 Scale structure
16.6.1.1.1.1 Scale structure
16.6.1.1.1.1.1 Information about this scale
Dataframe: | res$data |
Items: | highDose_AttGeneral_good, highDose_AttGeneral_prettig, highDose_AttGeneral_slim, highDose_AttGeneral_gezond & highDose_AttGeneral_spannend |
Observations: | 303 |
Positive correlations: | 10 |
Number of correlations: | 10 |
Percentage positive correlations: | 100 |
16.6.1.1.1.1.2 Estimates assuming interval level
Omega (total): | 0.79 |
Omega (hierarchical): | 0.80 |
Revelle’s Omega (total): | 0.79 |
Greatest Lower Bound (GLB): | 0.87 |
Coefficient H: | 0.85 |
Coefficient Alpha: | 0.78 |
Note: the normal point estimate and confidence interval for omega are based on the procedure suggested by Dunn, Baguley & Brunsden (2013) using the MBESS function ci.reliability, whereas the psych package point estimate was suggested in Revelle & Zinbarg (2008). See the help (‘?ufs::scaleStructure’) for more information.