Hi Riccardo I got your details from the GRETL user community site. A great friendly product from a user perspective!

I have used a number of functions but mainly the logit regression and the Bayesian function. All good. However I noted that when the output for the logit function is saved in word and copied to an excel spreadsheet the signs are not proper minus signs. See below. GRETL OUTPUT Coefficient Std. Error z p-value V3D_A1_6 −175812 50541.4 −3.479 0.0005 *** compared to -175812 -3.479 Which means one needs to correct the output if further analytical work needs to be performed. Now, in an earlier version of GRETL the signs were in the correct format !............ so may be a suggestion to correct this. The sign has remained unchanged for quite some time now.

Another suggestion would be to add a stepwise function (backward or forward) for sequential addition/deletion of variables to determine the final logit model (example in the binary logit) with the existing p-values (say 0.1) as the criteria of adding (or removing) significant variables. This is similar to functions/options available in SPSS, Statgraphics, Stata and other packages. This would greatly assist a user identify the significant variables and model quicker. Admittedly this will add to the processing time and memory to the final output. However it will definitely be a big improvement and if it is added to the binary logit function as an option in the menu like other software packages (compared to a separate function package) even better!. Currently this is a very manual repetitive process of removing each non-significant variable from the model, especially if the list of regressors is large and therefore time consuming. I noted that there is a function package available for sequential variables, however this is only for OLS not other functions such as binary logit. Also the function seems to require a list 1 of initial regressors and then the candidates. What if all regressors are candidates to begin with......Also there does not appear to be p-value criteria which is a standard feature in most packages.

I hope my input is useful