I am currently looking into the process tool by hayes. I have installed it and would like to have more than 1 independent and dependent variable. Is there any way to add more than one independent and dependent variable? The tool only allows 1 for each in spss.

If not, can anyone recommend me a statistical programme that could do this kind of analysis?

Thanks in advnace ]]>

i am a newbie here. my supervisor wanted me to categorize my IV and then do linear regression (so my DV is continous). All was fine but now she wants me to test for trend. I am really confused what she means by that... Her phd student mentioned that I need to find the medians for each of the quartiles and then use those... to calculate the trend. Not really sure what exactly she means. Anyone has any ideas?

sorry if that sounds dumb but i am having a hard time understanding this :shakehead and my supervisor isnt really helpful as she is expecting me to know this stuff already (where from, i dont know):shakehead:shakehead:shakehead ]]>

I've been cracking my brain on how to solve this SPSS issue. I've learned SPSS on my own, and don't have an extensive stats background, but I'm familiar with the basics. I've attached the SPSS clusters exported to excel files.

Problem: I'm trying to create customer segmentation models based on survey data. I have 3 sets of data. I'm using Data Set A as the existing cluster model through which to apply Data Set B and C, but the results I'm getting just don't seem to make sense based on historical data we've collected.

Here's what I did:

1) Identified the optimal # of clusters using Wards' method on SPSS, plotting the scree diagram, and identifying the elbow point. Optimal # of clusters is 4.

2) Prepped Data Set A for SPSS. Identified statistically significant variables to use for analysis. Ran K-Means clustering on Data Set A to classify cases into each cluster. This is successful. Cases are clustered into 4 different groups.

3) Prepped Data Set B and C for SPSS. Matched variables so it aligns with Data Set A. Ran K-Means clustering on Data Set B and C using the saved Data Set A cluster model. This is where it gets weird. All cases in Data Set B and C are clustered into 1 group. Based on historical data + excel analysis, it just doesn't make sense for both sets of data to all belong in 1 cluster.

I've tried cleaning up the data and eliminating outliers that could skew the data. I've rerun the analysis multiple times. I've conferred with multiple people. It seems the process is solid.

What am I overlooking? Is it just because this data isn't prepped well enough to run K-means clustering on SPSS?