I forgot to add. How can I estimate cluster-robust standard errors and 95%
confidence intervals for odds ratios?
Thank you,
Wander
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Thanks for your prompt responses. I will look at the readings you sugggest.
One quick question, sampling weights can be applied in clmm2?
Thank you,
Wander
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Yes; see clm and clmm2 (mixed effects) in the ordinal package for
fitting proportional odds models. See section 3 of
http://cran.r-project.org/web/packages/ordinal/vignettes/clm_tutorial.pdf
to see how to test the proportional odds assumption with clm - it is
equivalent for clmm2 models. For an int
-boun...@r-project.org] On
Behalf Of shkingdom
Sent: Saturday, 1 March 2014 11:57
To: r-help@r-project.org
Subject: [R] Multilevel analysis for ordinal responses
Dear all,
I need to fit a multielvel model for an ordinal response. Does R have a
command for conducting a multilevel ordinal logistic
Dear all,
I need to fit a multielvel model for an ordinal response. Does R have a
command for conducting a multilevel ordinal logistic regression when the
model violates the parallel regression or proportional odds assumption?
Additionally, are there any tests to check the parallel regression
assu
Thanks for your comments, David and Bert.
The best would be to provide an example. Let's say we have a dataset like
this one:
IDEmployee Company OU CountViewPortal CountLogin TimeOnTask Performance
1 Company1 Company1.OU1 21 33 627.8 4.3
2 Company1 Company1.OU2 45 54 34.8 2.3
3 Company2 Company1.OU
On Sep 30, 2013, at 3:22 PM, srecko joksimovic wrote:
> I thought so, but then I found this:
> "Normality
> The assumption of normality states that the error terms at every level of the
> model are normally distributed"
> maybe I misinterpreted something.
Notice that it is the _error_terms_ th
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of srecko joksimovic
> Sent: Monday, September 30, 2013 3:22 PM
> To: David Winsemius
> Cc: R help
> Subject: Re: [R] multilevel analysis
>
> I though
I thought so, but then I found this:
"Normality
The assumption of normality states that the error terms at every level of
the model are normally distributed"
maybe I misinterpreted something.
On Mon, Sep 30, 2013 at 3:06 PM, David Winsemius wrote:
>
> On Sep 30, 2013, at 2:50 PM, srecko joksim
On Sep 30, 2013, at 2:50 PM, srecko joksimovic wrote:
> I have an example of multilevel analysis with 3 levels, but data are
> non-normally distributed. In case of normal distribution, I would perform
> multilevel linear analysis using lme function, but what should I do in case
> of non-normal di
I have an example of multilevel analysis with 3 levels, but data are
non-normally distributed. In case of normal distribution, I would perform
multilevel linear analysis using lme function, but what should I do in case
of non-normal distribution?
thanks,
Srecko
[[alternative HTML version
Hi,
i am trying to learn something about multilevel analysis using a great
"Discovering statistics using R". I constructed some sample data and then
tried to fit a model. Generally model fits well, however when trying to fit
the same model using z-score (standarizded) variables i got an error:
Er
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