Dear all,
Thanks to everyone who replied off list to my (rambling) question
earlier this year! I have put pointers to things I found useful over
here:
http://tinyurl.com/yvvvn9
Thought it might be helpful to share as now and again I receive
emails from people wondering if I ever made progress.
Best wishes,
Andy
On 25 Feb 2007, at 19:58, Andy Fugard wrote:
> Dear all,
>
> I'm struggling to find the best (set of?) function(s) to do repeated
> measures logistic regression on some data from a psychology
> experiment.
>
> An artificial version of the data I've got is as follows. Firstly,
> each participant filled in a questionnaire, the result of which is a
> score.
>
>> questionnaire
> ID Score
> 1 1 6
> 2 2 5
> 3 3 6
> 4 4 2
> ...
>
> Secondly, each participant did a task which required a series of
> button-pushes. The response is binary. The factors CondA and CondB
> describe the structure of the stimulus:
>
>> experiment
> ID CondA CondB Response
> 1 1 a1 b1 1
> 2 1 a2 b2 0
> 3 1 a3 b1 0
> 4 1 a4 b2 0
> 5 1 a1 b1 1
> 6 1 a2 b2 0
> 7 1 a3 b1 0
> 8 1 a4 b2 0
> 9 2 a1 b1 1
> 10 2 a2 b2 0
> 11 2 a3 b1 0
> 12 2 a4 b2 0
> 13 2 a1 b1 1
> 14 2 a2 b2 0
> 15 2 a3 b1 0
> 16 2 a4 b2 0
>
> I would like to model how someone's score on the questionnaire
> relates to the responses they give in the button-pushing. I'm
> particularly interested in interactions between the type of the
> stimulus and the score.
>
> I combined the experiment and the questionnaire dataframe with a
> merge so now there an additional column.
>
>> exp.q
> ID Score CondA CondB Response
> 1 1 6 a1 b1 1
> 2 1 6 a2 b2 0
> 3 1 6 a3 b1 0
> 4 1 6 a4 b2 0
> 5 1 6 a1 b1 1
> 6 1 6 a2 b2 0
> 7 1 6 a3 b1 0
> 8 1 6 a4 b2 0
> 9 2 5 a1 b1 1
> 10 2 5 a2 b2 0
> 11 2 5 a3 b1 0
> 12 2 5 a4 b2 0
> ...
>
> Eventually, via glm, glmmPQL, and a few others, I ended up with
> lmer. My questions follow. I suspect (or hope) that I need to be
> pointed towards the relevant literature. I own Faraway's
"Extending
> the Linear Model with R" and Crawley's "Statistics: An
Introduction
> using R".
>
> 1. Is the way I've combined the tables okay? I'm concerned that
the
> repetition of the score is Bad but can't think of any other way to
> code things.
>
> 2. Is lmer the most appropriate function to use?
>
> 3. If so, does the following call capture what I'm trying to model?
>
> model1 = lmer(Response ~ CondA * CondB * Score + (1|Subject),
> data =exp.q,
> family = binomial)
>
> I just want to tell lmer, "Look, this set of responses all comes from
> the same person: tell me the within-subject stuff that's going on and
> how that's affected by their score!"
>
> 4. Is there any way to do stepwise model simplification? In the real
> data I have, there are several more predictors, including more than
> one questionnaire score and subscores. I have specific hypotheses
> about what could be going on, so I can live with manual editing of
> the formulae, but it's nice for exploratory purposes to do stepwise
> simplification.
>
> 5. What's the best way to discover and report the relative
> contribution of each predictor? I'm after an analogue of
> standardized betas (though I recently learned that they're thoroughly
> evil).
>
> 6. Is there anyway to get a p-value for goodness of fit?
>
> Many thanks for any help,
>
> Andy
>
> --
> Andy Fugard, Postgraduate Research Student
> Psychology (Room F15), The University of Edinburgh,
> 7 George Square, Edinburgh EH8 9JZ, UK
> Mobile: +44 (0)78 123 87190 http://www.possibly.me.uk
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-
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> and provide commented, minimal, self-contained, reproducible code.
--
Andy Fugard, Postgraduate Research Student
Psychology (Room F15), The University of Edinburgh,
7 George Square, Edinburgh EH8 9JZ, UK
Mobile: +44 (0)78 123 87190 http://www.possibly.me.uk