Multinomial Logistic Regression

#1
Hello everyone,

I'm trying to solve a statistical problem in my research. The research was conducted to test the relationship between the experience (happy, unhappy) of a traveller and his awareness of digital communication channels in the airport. My dependent variable consists of 3 responses from 200 people; happy, unhappy and neutral. The predictor is the number of digital channels that they are aware of (total of 9). There are several other variables that have also been taken into account, such as age, sex, Residence (dummy variable), whether travelling first time (dummy variable), travel purpose (dummy variable), place where data was collected such as ticketing, baggage claim, parking lot etc. (categorical variable) and whether travelling with a companion (dummy variable). My hypothesis is that awareness of digital communication channels improves the quality of experience (happy unhappy or neutral).
I want to perform regression analysis to see test my hypothesis and also to see which of the predictors are the strongest. I tried Multinomial logistic regression I get a statistically significant model, however none of the parameter estimates are significant. I feel that the problem might be because my three groups (happy, unhappy and neutral) are unequal in size (happy = 125, unhappy=33 and neutral = 42). How do I carry on a meaningful regression analysis?
 
#2
Hi Praveena,

Did you do a power analysis to ensure that the sample is big enough?
Can you please show us the results?

Generally, If you have a good theoretical reason to include a variable in the model you shouldn't exclude it only because it is statistically insignificant. So you overall model is significant.
On the other hand, if you bomb your model with many irrelevant predictors, you may find yourself with a significant model which is not correct ...