# Chapter 4: Structural Equation Models

### Example 2 on Structural equation modelling: The same model fitted separately for different countries

Fit the model considered in Example 1 separately for data from each of the countries in the ESS, and compare the results.

R commands:

As one illustration of the results from this analysis, Table 4.1 shows the estimated regression coefficients and their levels of significance for the structural model for Co-operation with the police. Because these models were estimated separately for each of the countries rather than in one multigroup model, the scales of the latent variables are not here fixed to be comparable. The exact values of the regression coefficients can thus not be compared between the countries. However, we can compare the qualitative patterns of the results, for example the signs and levels of significance of the same coefficient in different countries.

There is a fair amount of variation in the levels of significance of the coefficients, in that each of the explanatory factors is a significant predictor of willingness to co-operate in many countries, but none of them in all countries. The variable which is significant in the largest number of countries is the personâ€™s trust in the procedural fairness of the police. The directions of the associations are consistent in the sense that where a coefficient is significant it has the same sign in all the countries, with the one exception of trust in the effectiveness of the police which has a significantly negative coefficient in some countries and a significantly positive one in others.

*Table 4.1: Estimated coefficients for the structural model for the factor on Willingness to co-operate with the police, estimated as part of the structural equation model shown in Figure 4.1, separately for each country in the ESS.*

Coefficients in the model for Co-operation: |
||||
---|---|---|---|---|

Country | Effectiveness | Procedural fairness |
Obligation to obey |
Moral alignment |

Belgium (BE) | -0.005 | 0.089 | 0.007 | 0.047 |

Bulgaria (BG) | -0.028 | 0.148** | 0.024 | 0.075** |

Switzerland (CH) | -0.078 | 0.197** | 0.004 | 0.028 |

Cyprus (CY) | -0.124* | 0.249*** | -0.050 | -0.063 |

Czech Republic (CZ) | 0.012 | 0.123** | 0.023 | 0.086** |

Germany (DE) | 0.030 | 0.130*** | -0.001 | 0.053* |

Denmark (DK) | -0.126** | 0.123* | 0.123*** | 0.063 |

Estonia (EE) | -0.091 | 0.243*** | 0.054 | 0.102** |

Spain (ES) | -0.040 | 0.141* | 0.046 | -0.021 |

Finland (FI) | -0.125** | 0.137** | 0.144*** | 0.098** |

France (FR) | -0.163** | 0.174** | 0.071* | 0.051 |

United Kingdom (GB) | -0.089* | 0.222*** | 0.106*** | -0.022 |

Greece (GR) | 0.091* | 0.074 | -0.018 | 0.012 |

Croatia (HR) | 0.066 | 0.138* | -0.019 | -0.034 |

Hungary (HU) | -0.049 | 0.073 | 0.113*** | 0.090* |

Ireland (IE) | 0.010 | 0.126** | 0.013 | 0.124*** |

Israel (IL) | -0.045 | 0.100* | 0.137*** | 0.008 |

Lithuania (LT) | 0.107* | -0.007 | 0.016 | 0.039 |

Netherlands (NL) | -0.049 | 0.135** | 0.104*** | -0.005 |

Norway (NO) | -0.115** | 0.116 | 0.050 | 0.130** |

Poland (PL) | -0.094* | 0.094 | 0.027 | 0.047 |

Portugal (PT) | -0.029 | 0.023 | 0.005 | -0.012 |

Russia (RU) | 0.063 | 0.094* | 0.016 | 0.022 |

Sweden (SE) | -0.088* | 0.166* | 0.077* | 0.047 |

Slovenia (SI) | 0.137** | 0.027 | -0.100** | -0.025 |

Slovakia (SK) | -0.004 | 0.248*** | 0.023 | -0.054 |

Ukraine (UA) | -0.052 | 0.106* | -0.023 | 0.096** |

*Note: ***: p<0.001; **: p<0.01; *:p<0.05*