FAQ PROCESS To Tackle The Challenges Of The Templates And Focus On Your Research

Frequently Asked Questions about how to use the PROCESS templates

moderated mediation model 14 PROCESS

This FAQ PROCESS overview can hopefully help you to use my templates to graph conditional effects. They are made for the PROCESS macro from Andrew Hayes to calculate conditional effects within SPSS.

Current available PROCESS templates

Current PROCESS blogs

For an example how to use this template, you are welcome to read our blogs:

https://www.md2c.nl/graphing-moderation-of-process-v3-0-model-1/

https://www.md2c.nl/graphing-conditional-indirect-effects/

I am very thankful for all the great feedback and questions we are receiving from fellow-researchers, and I hope that you will continue doing this.

With this list of Frequently Asked Question, I am trying to cover most of the questions, but please don’t hesitate to reach out to me!

FAQ PROCESS Questions & Answers

FAQ PROCESS Question: I can’t see any graph, what goes wrong?

Answer: Please check first if you have “.” or “,” as a decimal separator. The templates require a “.” as decimal separator. A quick solution could be the usage of “find-and-replace” in Excel, where you replace the “,” for the “.” for the input rows. Secondly, please check the axis of the graph: sometimes you have to reset them by right-clicking on the required axis, select “Format Axis”, and reset the Minimum and/or Maximum Bounds values.

FAQ PROCESS reset axis bound

FAQ PROCESS Question: The axis are crossing the middle of the graphs (mostly at value 0), what can I do?

Answer: you can right-click on the required axis, select “Format Axis”, and set the value at which the axis crosses

FAQ PROCESS set axis

FAQ PROCESS Question: There isn’t a template for my model, can you make one?

Answer: if you could contact us, and provide us the data (we won’t use it other than just for inspection and possible creation of the template), we can let you know if that is possible or not.

FAQ PROCESS Question: I haven’t received the download link, what can I do?

Answer: it could take some business days to process the paypal transfer, but sometimes, the email is in your spambox of emails are blocked. In any case: please feel free to reach out to me and I will make sure you will get your template. You can reach me by sending an email to info [at] md2c [dot] nl

FAQ PROCESS Question: I can’t download the template, what can I do?

Answer: please check your browser. The download works best with Mozilla or Edge, and does not work correctly with Chrome currently. In any case: please feel free to reach out to me and I will make sure you will get your template. You can reach me by sending an email to info [at] md2c [dot] nl

 

Human Resources Analytics – Predict Employee Leave

Human Resources Analytics - Why are employees leaving

Imagine you are an HR-Manager, and you would like to know which employees are likely to stay, and which might leave your company. Besides you would like to understand which factors contribute to leaving your company. You have gathered data in the past (well, in this case Kaggle simulated a dataset for you, but just imagine), and now you can start with this Hands On Lab – Predict Employee Leave to build your prediction model to see if that can help you.

In this lab, you will learn how to create a machine learning module that predicts whether an employee will stay or leave your company. We are aware of the limitations of the dataset but the objective of this hands on lab is to inspire you to explore the possibilities of using machine learning for your own research, and not to build the next HR-solution.

We created a starting experiment for you on the Azure AI Gallery to give you a smooth start. Continue reading “Human Resources Analytics – Predict Employee Leave”

Graphing moderation of PROCESS v3.0 Model 1

Graphing moderation with PROCESS V3.0 graph 2

This blog is about graphing moderation with the help of SPSS with the PROCESS macro, and our corresponding MD2C Graphing template for PROCESS v3.0 Model 1 – Moderation.

The case that we used is based on the article of Chapman and Lickel (2016), and you can find a detailed elaboration of this case in Andrew Hayes’ second book about Introduction to Mediation, Moderation, and Conditional Process Analysis (Hayes, 2017). You can download the data from Hayes’ website. The datafile you need for this example is called DISASTER. Besides, you can also download the PROCESS V3.0 macro for SPSS and SAS (and much more) from the site: http://www.processmacro.org/

Continue reading “Graphing moderation of PROCESS v3.0 Model 1”

The effect of Stress on Satisfaction and Self-Evaluation

Stress, Satisfaction and Self-Evaluation

This short blog is about exploring the relationships between stress, satisfaction and self-evaluation. For an assignment of the course Introduction to Psychology, I had to gather 20 responses to answer some questions. Due to the huge amount of responses, I thought it could be nice to share the results to thank all of you for your participation. Continue reading “The effect of Stress on Satisfaction and Self-Evaluation”

Predictive modeling and human interaction

Reflection predictive modeling. Credits to Olu Eletu

This blog gives you some reflections on predictive modeling and human interaction.

The prediction…

The nice thing of predictive modeling is that it gives you possible answers, which you could use to define you or your customers’ actions. You can classify things or trying to predict numbers, like your sales. Another nice thing is that you can retrain your models over time to get -hopefully, but not guaranteed- better results. Continue reading “Predictive modeling and human interaction”

Optimizing prediction models on Azure – pruning the trees

Optimizing prediction models on Azure

This is a simple example about optimizing prediction models on Azure. In this case we will use a Boosted Decision Tree model. We will show you how you can use the Permutation Feature Performance module to prune your trees.

We start with the Student Performance Classifier from a previous blog. We already found out that the Boosted Decision Tree algorithm gave the best results, so we will start with that one to train our model with. Continue reading “Optimizing prediction models on Azure – pruning the trees”