# Comparing a Fuzzy Hybrid Approach with Invariant MGCFA to Study National Identity
## 2. Nationhood as a Construct
Now, we analyse pragmatically how different authors have developed the national identity construct based on ISSP data. In all the cases, the operational definition of national identity was based on the responses given to the question: \"Some people say that the following things are important for being truly [country-fellow]. Others say they are not important. How important do you think each of the following is? Citizens, then, rate eight indicators from \"not important at all\" to \"very important\". There have been different methods to analyse national identity such as simple average means, single indicators, EFA, CFA, and MGCFA. For example, [PERSON] et al. [29] analysed the national identity using 31 countries and ISSP 2003 wave, excluding from the dataset the observations with missing values and those citizens who did not possess the citizenship of the country. The authors did not apply any multivariate analysis and they construct the national identity using three of the items discussed in the nationalism literature: citizenship (civic), language (cultural) and ancestry (ethnic). They preferred to use this approach because EFA provided very inconsistent results regarding the factor structures across the 31 countries. Exploratory factor analysis (EFA) has been usually first applied to obtain very different patterns of factor composition that ranges from one to three factors. The factors have been mainly named as ethnic and civic. Some studies have analysed different countries or countries with different ethnic groups, so EFA have been performed for different groups, and the results obtained also present many differences: stable results [3; 7]--for the pool dataset, same structure with different factor loadings [7]--for different countries and different structure [24; 25; 26; 29]. In all the cases, the main differences were caused by the number of countries or by the different ethnic groups that exist in multinational countries. [PERSON] and [PERSON] [24] showed that the two dimensions of national identity (ethnic vs. civic) did not homogeneously exist in 19 European countries using the ISSP 2003 wave. In fact, the authors found that for seven countries the national identity can be studied with only one factor. For the whole sample, two items, citizenship and feeling, presented high load factors in both dimensions, so the authors concluded that the neat political distinction proposed by the theory was not real at all but was only a non-confirmed illusion. They showed that the distinction between some attributes belonged more to their characteristics regarding whether some of them can be either considered as more or less ascribed or can be related to social and political involvement. After EFA, the most common method applied has been CFA, in which cross-national measurement equivalence has been analysed through MGCFA. [PERSON] [3] included 31 countries in the analysis and began by including only one latent construct to extremely differentiate credentialists from those who are post national individuals. In a second model, two latent constructs were analysed to represent ethnic and civic dimensions. Interestingly, the author found that the two factor solutions was mainly due to two indicators, respect (civic dimension) and ancestry (ethnic dimension). The other six indicators were included in both dimensions. The author also used a multilevel regression to show that national identity affects public policy preferences related to immigration, citizenship, assimilation, and foreign policy. [PERSON] et al. [25] showed that some differences between countries were due to response rates and other features of survey design and that validity of cross-national comparisons can be jeopardized if some of the existing methodological problems are ignored. The authors showed that several items did not mean the same thing in all countries, so there were lessons to be learnt such as non-response bias or measurement errors to make the results comparable at national level.