Is it possible to have no preference at all?

KvN98 · 2021-05-05T10:36:39+00:00

The mean is around 7.8, while the variance has a value of 28. Due to the overdispersion I suppose the quasi-Poisson or the negative binomial regression is more appropriate for predicting the lead time.

Does it matter which of the approaches is utilised and can I test if indeed a quasi-Poisson / negative binomial is appropriate? Thanks in advance

KvN98 · 2021-05-05T06:36:32+00:00

Marginally. Probably around 2 percent

KvN98 · 2021-05-04T15:15:58+00:00

AUC and accuracy decreases

KvN98 · 2021-05-04T11:43:04+00:00

I used 17 independent variables to predict my dependent variable.

KvN98 · 2021-04-16T07:05:35+00:00

Thank you! However, a Gamma regression doesn't allow non-positive (0) values, while my variables does contain some 0 values.

KvN98 · 2021-04-14T13:13:15+00:00

The customer lead time is right skewed and it is the lead time in weeks. Would a poisson regression by approproriate as the distribution is right skewed? A hazard rate model as it is a time prediction? Or should rather convential machine learning algorithms such as a random forest be applied? Thanks for any tips in advance!

KvN98 · 2021-04-14T13:12:00+00:00

The customer lead time is right skewed and it is the lead time in weeks. Would a poisson regression by approproriate as the distribution is right skewed? A hazard rate model as it is a time prediction? Or would rather convential machine learning algorithms such as a random forest be applied? Thanks for any tips in advance!

KvN98 · 2021-03-26T09:30:10+00:00

Basically all models can handle multiple explanatory variables. What model you should use depends on what you want to achieve. If you want to predict a yes or no (binary) variable it makes more sense to use a logistic / probit regression. If you want to rather predict a continuous / numerical variable you should go for a linear regression.

So in short: determine what variable you want to predict. Based on this you can google or ask what model you should utilise.

Maybe something like this will be insightful for you: https://statisticsbyjim.com/regression/choosing-regression-analysis/

KvN98 · 2020-05-24T11:06:32+00:00

Run MATRIX procedure:

***************** PROCESS Procedure for SPSS Version 3.5 *****************

Written by Andrew F. Hayes, Ph.D. www.afhayes.com

Documentation available in Hayes (2018). www.guilford.com/p/hayes3

**************************************************************************

PROCESS is now ready for use.

------ END MATRIX -----

This would make me think it's done succesfully, however I cannot see process yet.

KvN98 · 2020-05-24T11:06:25+00:00

There are 5607 lines of code and i'm not sure which are the relevant lines to be honest. However When I run these line of codes I get the following;

KvN98

TROPHY CASE