Using the attached data, I am working on the effects of poverty on farmers' adaptive capacities (N=1211). Multivariate analysis is used to isolate interactions between different determinants. My dependent variable (nb_success) measures the number of changes in agricultural practises. The variable is bounded (0-9) and a binomial distribution with a logit link function fits the data well.
However, I have an issue with the poverty variable (DEP_TOT). When running the regression with other determinants, the variable has zero degrees of freedom and SAS displays a value of zero for both the parameter estimate and its standard error
I used the following SAS command where nb_trials is =5:
proc genmod data= data1 ; model nb_success/nb_trials = m002 Dist_marche SS_nb_s SS_part_travaux_agri SS_CeRPA m104 com dep_tot m15 i705 PART_ASSO part_ceremonies i102 i101 Educ p_sp p_temp/ dist=bin link=logit ;run;
My understanding is that SAS finds (DEP_TOT) to be linearly dependent, or aliased, with columns corresponding to parameters preceding it in the model. However, when I run the model with this variable as a unique predicator, the problem persists. Another variable (number of childrens in the households) is correlated with this variable. When I drop the number of children, the issue remains. The model works well when DEP_TOT is log transformed or stratified in deciles and even quartiles.
Any idea where the issue may lies? Would log-transform an independant variable in a GLM be an issue?
Many thanks for your help, I am confused