Dear Shashidhar Belbase maybe this article can be useful for you:

Currie, I. D., Durban, M., & Eilers, P. H. C. (2006). Generalized linear array models with applications to multidimensional smoothing. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 68(2), 259–280. doi:10.1111/j.1467-9868.2006.00543.x

You can read github discussions as well: https://github.com/search?q=SPSS

Dear Shashidhar Belbase,

I hope this may be useful for you:

https://www.amazon.com/How-General-Linear-Model-SPSS/dp/1973468050

With best regards,

Firdos

Dear Shashidhar Belbase, the following link briefly describe how to run GLMs in SPSS.

https://www.ibm.com/docs/en/spss-statistics/27.0.0?topic=statistics-generalized-linear-models

If you want to know more about GLMs, this book might come in handy

https://www.amazon.com/Introduction-Generalized-Chapman-Statistical-Science/dp/1584889500

I would not look for a book on GLM specific to SPSS. Just use a good statistics book on the topic (that uses no package, or any package) and if the students understand the statistics the SPSS help pages are good enough to allow students who understand the concepts to apply these.

Thank you all for your suggestions/opinions with potential resources. Please, be specific to SPSS for GLM or GLM with SPSS in your suggestions.

I agree with Daniel Wright, the package is secondary. This may help you:

Generalized Linear Models With Examples in R

Peter K. Dunn, Gordon K. Smyth

Disclaimer: I was completely unaware of this book until I found it a few moments ago. So please do not consider this a recommendation or endorsement of the book. Having said that, it looks like it might be the sort of thing you're seeking, Shashidhar Belbase.

Orme, J. G., & Combs-Orme, T. (2009). Multiple regression with discrete dependent variables. Oxford University Press.

• https://oxford.universitypressscholarship.com/view/10.1093/acprof:oso/9780195329452.001.0001/acprof-9780195329452
• https://global.oup.com/us/companion.websites/9780195329452/

The following summary is copied from amazon.ca.

Most social work researchers are familiar with linear regression techniques, which are fairly straightforward to conduct, interpret, and present. However, linear regression is not appropriate for discrete dependent variables, and social work research frequently employs these variables, focusing on outcomes such as placement in foster care or not; level of severity of elder abuse or depression symptoms; or number of reoffenses by juvenile delinquents in the year following adjudication. This book presents detailed discussions of regression models that are appropriate for a variety of discrete dependent variables. The major challenges of such analyses lie in the non-linear relationships between independent and dependent variables, and particularly in interpreting and presenting findings. Clear language guides the reader briefly through each step of the analysis, using SPSS and result presentation to enhance understanding of the important link function. The book begins with a brief review of linear regression; next, the authors cover basic binary logistic regression, which provides a foundation for the other techniques. In particular, comprehension of the link function is vital in order to later interpret these methods' results. Though the book assumes a basic understanding of linear regression, reviews and definitions throughout provide useful reminders of important terms and their meaning, and throughout the book the authors provide detailed examples based on their own data, which readers may work through by accessing the data and output on companion website. Social work and other social sciences faculty, students, and researchers who already have a basic understanding of linear regression but are not as familiar with the regression analysis of discrete dependent variables will find this straightforward pocket guide to be a terrific boon to their bookshelves.

You might also say something about your students (are they PhD stats students, are they social science students, etc.). What books will vary accordingly.

Dear Prof. Shashidhar Belbase, I think one of the best books you can easily find on GLM is Field, A. (2018). Discovering statistics using IBM SPSS statistics. London, SAGE Publication Ltd. Earlier editions of the book are okay too. The book is very good with sample data and practical analyses on interesting examples using SPSS.

Thank you Dr. Zakariya for your recommendation. - Shashidhar@