[R-sig-ME] Linear mixed effects
Steve.Pierce at cstat.msu.edu
Fri Mar 24 13:35:00 CET 2017
The sort of model you're fitting is often called a growth curve model. The first half of following book is an excellent source on these sorts of models. It gives great descriptions of how to specify & interpret such models. They use lots of graphs to help visualize different model specifications and results. Example code for the text book is available online at http://stats.idre.ucla.edu/other/examples/alda/ as well.
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York, NY: Oxford University Press.
Steven J. Pierce, Ph.D.
Acting Director; Associate Director
Center for Statistical Training & Consulting (CSTAT)
Michigan State University
E-mail: Steve.Pierce at cstat.msu.edu
From: Victoria Stimple [mailto:victoriastimple at gmail.com]
Sent: Wednesday, March 22, 2017 8:19 PM
To: R-SIG-Mixed-Models at R-project.org
Subject: [R-sig-ME] Linear mixed effects
Hi all, I am writing to receive some help on the following issue:
I want to estimate different slopes and intercepts for the three groups.
For example: group A is subjects whose father's were blue-collar; group B
is subjects whose father's were white-collar; group C is subjects whose
father's were other types of workers. I have repeated measures for 10
annual surveys and subjects reported how much of their income they saved. I
want to see if the intercept and trajectory differs for the three groups.
This is what I come up with but I am not sure if this gets at the
appropriate verbal explanation. Thank you very much for your time. I truly
appreciate it. Thank you!
m1 <- lmer(savings~ time + (time|subjects))
m1 looks at the impact of time on savings and estimates intercepts and
slopes for each subject.
m2 <- lmer(savings~time*fathers_occupation + (time|subjects))
Does m2 examine the differences in the intercept and slope for the two
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