I want to use a generalized linear model, with the fraction of the people going to a pub(first column) as the response and the discount level (second column) as a fixed factor, to see if the model is significantly different than a null model.
g = fitglm(a(:,1),[a(:,2),a(:,3)],'linear','distr','binomial','link','probit')
I got the following results from the analyis;
Generalized linear regression model:
________ _________ _______ ________
(Intercept) -1.4245 0.64976 -2.1923 0.028356
x1 0.00651 0.0071339 0.91255 0.36148
35 observations, 33 error degrees of freedom
Chi^2-statistic vs. constant model: 0.869, p-value = 0.351
Does this mean that there is a significant difference between the null model and the GLM?, And the 'fraction of people going to the pub' can be predicted using a linear model with varying access levels? Why there is a large degree of freedom, eventhough i only have 4 'discount levels' ?Data is provided for a reference.
Any help will be appreciated..