[R-sig-ME] measuring carry-over effects in mixed models
@|m@h@rme| @end|ng |rom gm@||@com
Wed Mar 2 06:53:38 CET 2022
Thank you for your response. Could you possibly elaborate on
"Depending on the exact nature of the carryover effect"?
Also, how are the "lead/lag predictors" often created?
My data has the following general structure.
student group time
1 C 0
1 C 1
1 C 2
1 C 3
1 T 0
1 T 1
1 T 2
1 T 3
2 C 0
2 C 1
2 C 2
2 C 3
2 T 0
2 T 1
2 T 2
2 T 3"
data <- read.table(text=m,h=T)
On Tue, Mar 1, 2022 at 11:12 PM Phillip Alday <me using phillipalday.com> wrote:
> Depending on the exact nature of the carryover effect, the usual
> suspects would be:
> 1. using an autoregressive model of some type
> 2. including lead/lag predictors in your model, e.g.
> lmer(y ~ time*group*prev_time + [covariates] + (1 | student))
> But note that the initial timepoint doesn't have a prev_time and so
> there is a missing value there.
> On 17/2/22 12:32 pm, Simon Harmel wrote:
> > Hello All,
> > I'm analyzing the data from my longitudinal study whose design can be
> > depicted as (view the following in plain text):
> > O1 X1 O2 X2 O3 X3 O4
> > O1 O2 O3 O4
> > where Xs denote subtitled videos given to the treatment group and Os
> > denote measurement occasions.
> > My current model is: lmer(y ~ time*group + [covariates] + (1 | student))
> > However, I'm also interested in measuring the "carry-over effects" of
> > watching subtitled videos at each occasion to the subsequent
> > occasions.
> > For instance, I want to know how much watching the subtitled video at
> > the first occasion (O1) impacts the treated students' performance at
> > later occasions (O2 and O3) etc.
> > I wonder if any changes to my model can enable me to measure these
> > carry-over effects or if any other R package may provide such
> > functionality?
> > Many thanks,
> > Simon
> > _______________________________________________
> > R-sig-mixed-models using r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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