How to Model The Passenger Experience For Specific Flights?

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We are analyzing airline industry data, where we have data on the passenger experience related to specific flights.  We have
data from about 50,000 passengers, drawn from 10,000 flights, of 20 airlines.  So far a regular 3 level HLM model.

We would like to see if the cultural values of the individual passengers effect the manner in which they assess their experience.  The passengers are drawn from multiple countries, and each country has different airline flying in an out.  As such, the countries are embedded within the airlines, and vice-versa.

We are trying to figure out the best way to specify this model.  Can we treat the cultural values of the passengers (i.e., country culture values as per Hofstede's work) as individual level variables, or do we need to specify a more complicated design for the model?  

Thanks in advance for your consideration.

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关键词：Experience Passenger Specific flights experie individual experience countries different industry

Hello

I am performing a two-level HGLM analysis with a binary outcome (with a random intercept, one random slope, no cross-level interactions) using HLM 6.0 software, and would like to calculate the proportion of total variance explained by the model. I'm using the method described by Snijders & Bosker (2012, p. 305), in which explained variance (sigma-squared F) is represented by the variance of the linear predictor.

Snijders & Bosker suggest the following calculation of the linear predictor (using the estimated coefficients for the intercept and slopes of level-1 predictors, and plugging in the values of the predictors):

Linear predictor = Gamma00 + Gamma10*X1ij + Gamma20*X2ij  (etc.).

Is it valid to also include the between-group variance explained, i.e. the model-estimated intercept for each group, in the calculation of the linear predictor? I'm wondering because it looks like the fitted values generated by HLM in the level-1 residual file (FITVAL) are adjusted by the Empirical Bayes estimate of the group intercept (EBINTRCP) like this:

fitted value = Gamma00 + EBINTRCP-j + Gamma10*X1ij + Gamma20*X2ij (etc.).

The proportion of total variance explained would then be calculated:

[Variance of fitted values] / ( [Variance of fitted values] + [residual between-group variance tau00] + [within-group variance 3.29] )

Is this a valid approach?
Thank you,