Country profiles

One of the most useful approaches to the data is to take a snapshot of a single country and look at how it fares in terms of different aspects of well-being – its well-being profile.

Let us for example take a closer look at Portugal (we have used SPSS):

  1. Subset the data to the Portuguese respondents.
  2. Switch on the design weight.
  3. Calculate the mean scores for the following components: positive feelings, absence of negative feelings, satisfying life, vitality, resilience & self-esteem, positive functioning, supportive relationships, and trust & belonging. If you want to have a more in-depth profile, then you could select further sub-components (for example different aspects of positive functioning).
  4. Copy the table from the output with all the means and paste it into an Excel sheet.
  5. Use Excel to create a ‘radar’ graph, below. From the menu, select ‘Insert’ – ‘Diagram’ - ‘Radar’.

Remember that 0 is the European average for any given component or sub-component.

Exercise 8

Create a ‘radar’ graph similar to the one in the figure above using data from a different country than Portugal.

You can do this with other sub-categories (e.g. age groups). It is also possible to plot more than one profile onto the same graph to allow direct comparisons. Why not calculate mean component scores for males and females for a given country, and plot the results?

SPSS syntax

*SPSS syntax for the example.

WEIGHT BY DWEIGHT.
COMPUTE filter_$=(CNTRY='PT').
VARIABLE LABEL filter_$ "CNTRY='PT' (FILTER)".
VALUE LABELS filter_$ 0 'Not Selected' 1 'Selected'.
FORMAT filter_$ (f1.0).
FILTER BY filter_$.
EXECUTE.
 
DESCRIPTIVES
VARIABLES=positive_affect negative_affect satisfaction vitality selfesteem functionings supportive_relations, trust_belonging
/STATISTICS=MEAN.
 
FILTER OFF.
USE ALL.
EXECUTE .
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