[Mediation-information] Trouble with mediate.ped function in Mediation for R

[Teppei Yamamoto]

Hi Greg,

The function can produce those values for the bounds when your data are 
not consistent with the identification assumptions, such as the 
consistency assumption or the exclusion restrictions. It could also be 
due to some mistake in the data (e.g. miscoding in a variable). If you 
send me your code and the dataset (maybe a subset that reproduces the 
same problem, if you cannot send the whole thing), I'll be happy to look 
into it to the extent I can.

We unfortunately don't have a plan to extend it to a continuous outcome 
variable, primarily because our theoretical framework doesn't simply 
generalize to such a setup. There are alternative approaches that could 
potentially achieve what we need, though, so we (or someone else) might 
someday get to it -- not on our immediate agenda unfortunately!

Best,
Teppei

------------------------------------------
Teppei Yamamoto

Associate Professor of Political Science
Alfred Henry and Jean Morrison Hayes Chair
Massachusetts Institute of Technology

http://web.mit.edu/teppei/www/
------------------------------------------

On 8/11/17 08:17, GREG PORUMBESCU wrote:
> Dear All,
> 
> My colleagues and I are trying to analyze data coming from a parallel 
> encouragement design using the mediate.ped function in the mediate R 
> package. Our encouragement, time, has three levels: 1 (long time), -1 
> (short time) and 0 (no time limit). We have two questions:
> 
> 1) We have followed the instructions provided in Tingley et al. 2014, 
> but when we run the syntax, the lower and upper bound confidence 
> intervals on all of the ACME report 0. These estimates hold even when we 
> used different (binary) mediators. The code we are using and the output 
> is as follows:
> 
>  > ped<- mediate.ped("PERFORMANCE_binary", "sum_obund_new_binary", 
> "negframe", "time", DFC_coded)
>  > summary(ped)
> 
> Design-Based Causal Mediation Analysis
> 
> Parallel Encouragement Design
> 
>                            Lower Bound Upper Bound
> Population ACME (control)           0           0
> Complier ACME (control)             0           0
> Population ACME (treated)           0           0
> Complier ACME (treated)             0           0
> 
> Sample Size Used:  610
> 
> 
> Would you have any idea what is causing our estimates to behave this 
> way? Any advice on how to resolve this issue?
> 
> 2) In our code, we transform our outcome variable, PERFORMANCE, into a 
> binary variable in order to run mediate.ped, as the instructions 
> indicate. However, is there any way to run mediate.ped with a continuous 
> outcome variable? If not, are there any plans to allow for this in the 
> future?
> 
> Many thanks,
> 
> Greg
> 
> Best wishes,
> 
> Gregory A. Porumbescu
> Assistant Professor
> School of Public Affairs and Administration
> Rutgers University Newark
> https://spaa.newark.rutgers.edu/gregory-porumbescu
> 
> https://scholar.google.com/scholar?hl=en&q=gregory+porumbescu&btnG=&as_sdt=1%2C14&as_sdtp=&oq=gre
> 
> 
> 
> ᐧ
> 
> 
> _______________________________________________
> Mediation-information mailing list
> Mediation-information at lists.r-forge.r-project.org
> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/mediation-information
>