SPSS tutorials for beginners PART 6 - Logistic regression models

In this SPSS tutorial for beginners, you will learn all about performing a logistic regression analysis. I will show you for which type of data this model is useful, how to set up your analyses and how to adjust for confounders.

About me:
I am a registered clinical epidemiologist and working as a fellow in medical oncology in the Netherlands. I have published over 50 manuscripts and have received several large research grants. I am particularly interested in research in geriatric oncology and am a an active member of the International Society for Geriatric Oncology.

You can find more information about my work on my linkedin page:

And here is my full bibliography:

Disclaimer:
Views and opinions are my own. Examples from clinical research will always include either my own work, or previously published research. I will include references in the description box.

[moraguardamagna]

Thank u so much!!! It is so clear :) Amazing

[henrykitunzi]

Thanks Nienke, this was helpful especially the categorical variable defining procedure and confounder adjustment. Could you please have another tutorial that covers the selection variable/ subgroups. Thank you in advance.

[iphonehelpcenter]

Thank Dr for doing this for free, this was really helpful.

By the way if you can tell me how can I find/access the data you just used in this video or share them in your description box that would be very much helpful so that we follow along.

Thanks again.

[rawiahnaoum]

This is very helpful. I have a question: I want to make two logistics model one for female and one for male, but the only variable that I have is Gender ? How can I do that ?

[humbertorodriguez]

Hi Nienke ! Thanks so much for your video! I am trying to understand which method should I choose for stepwise LR in SPSS. It offers Wald, LR and Conditional . Could you explain this please?

[leticiaalvarado]

Hi Nienke, amazing videos!! Would you be so kind to explain if age can be used as a continuos variable instead of categorical? Also can ordinal independent variables be used as continuous? like for example ECOG (1, 2, 3, 4). How is the output different if instead of using enter we use forward or backward? What do you recommend. Thanks for these very instructive videos

[zztzztzzttzztzzt]

Thank you for the video; at 1:31 you describe the variable "Age" with 5 or so different categories within; how did you make multiple categories within the same variable?

[fabdoc]

Thank you for great explanation. I have a question regarding interpretation of CI. What if the CI span 1 but the p value is <.05? Can we still consider the relationship statistically significant ?

[aracelimateosdiaz]

Thank you for your videos. Very clear explanation and very helpul to me. I have two questions: a) If you have one logistic regresion model without interactions and another with interactions, do you have to calculate ROC curve for both or just for the model without interactions? Many thaks