evankesteren
About
- Username
- evankesteren
- Joined
- Visits
- 22
- Last Active
- Roles
- Member
Comments
-
In order to get these metrics, you need to copy the lavaan code (check the "lavaan syntax" under options) to the structural equation modeling analysis. There, you can get all the fit metrics you need. In this blog there's more information …
-
Hey MarieLaure, you have some missing values, and the default full information maximum likelihood (FIML) handling of those missing values is only available with continuous endogenous variables. You can set the missing value handling to listwise dele…
-
Hi Maya, I understand that the difference can make things a bit confusing. Maybe the mediation analysis section of our blog can be a good starting point? In the end, both SPSS and JASP try to estimate the same thing: what is the indirect effect of X…
-
Hi Sarah, that's a great question. Including all three subscales as mediators would take into account the covariances among the mediators. The indirect effect of the subscale is then interpreted as "indirect effect given that the other subsca…
-
Hi Shani, indeed, the mediation analysis in JASP does not give standard errors and p-values for individual path coefficients currently. There is an issue here about this same problem. If you comment on that issue, the developers might give it higher…
-
Hi Mila, the first part of the mediation and moderation blog should describe exactly what you need: click. The covariates can just be added as additional predictors. Erik-Jan
-
Hi Alexander, yes, you should turn off FIML missing variable handling under "missing variables"! Then it should work. Erik-Jan
-
From the documentation at your link: fm="ols" differs very slightly from "minres" in that it minimizes the entire residual matrix using an OLS procedure but uses the empirical first derivative. This will be slower. and a bit lat…
-
-
Dear Sónia, you can choose - there's an option for percentile bootstrapping or for bias-corrected percentile bootstrapping. We do not have an option for bias-corrected accelerated bootstrapping: the bias-corrected option produces intervals using the…
-
Hi Jian, sorry for the delayed response! Here is an answer to your two questions and a more general answer: We have not provided a "method specification", but if you do want it you should submit an issue on our github. Then, the programme…
-
Hi Liesbeth, yes, you are correct - the R^2 value for each indicator is the proportion of variance accounted for by the latent factor (if the latent factor is the only thing this indicator is predicted by, otherwise it's just the proportion of var…
-
Hi @knappstein, Are you asking this because you have missing values in your dataset? I am working on an update that will display the sample size in the output :)
-
Hi mdt, these standard errors come from a sandwich estimator for the variance-covariance matrix of the coefficients. They are "default" Eicker–Huber–White standard errors for GLM. The precise implementation in R used for JASP, should yo…
-
Hi new2jasp, the mediation module is built on structural equation modeling in JASP. The PROCESS module works differently, using regressions. In many cases, they are exactly the same. Be careful entering your binary variables as scale variables in t…
-
Hi Katharina, yes, it's possible to get robust standard errors, under options -> confidence intervals / method -> robust. There the bootstrap option is also available! Erik-Jan
-
https://forum.cogsci.nl/uploads/647/RFWL28K8WJ8M.png Here is an example for you, with the csv below. Hope this helps! https://forum.cogsci.nl/uploads/567/NXPGZAC8WL9M.csv
-
Hi kszechy, this is currently not available, but it would be a really good feature to request! Could you submit it as a feature request on our GitHub page?
-
The round arrows indicate the estimated _residual variance_ of each variable, i.e., the total variance minus the variance explained by the other variables in the model. Since the predictor does not have variance explained by other variables, the res…
-
Yes, correct!
-
Hi ebenau, good to hear that you're liking the mediation analysis! The displayed effect estimates should be the same that you would get using the process macro. The direct effect from the predictor on the mediator is not displayed in the output, i…
-
Hi Miriam, Unfortunately this does not exist yet, indeed. We are going to work on a new-and-improved version of the SEM module soon, but until then the BC intervals are available in the mediation module only. If you want to make sure that this func…
-
This plotting functionality will be available in the soon-to-be released version 0.12 of JASP!
-
Sorry for the late response! What you find is strange, because in JASP the EFA parallel analysis is just a vanilla implementation of psych::fa.parallel(dataset) Looking at your plot, it could be that this difference is due to chance anyway (because …
-
You can find an answer to a similar question on this forum here: https://forum.cogsci.nl/discussion/5642/mediation-analysis-with-jasp-reporting
-
Hi Miriam, that's a very interesting difference, because not only the standard errors are different (which could potentially be due to choosing a different standard error method, bootstrap vs. normal), but also the parameter estimates (for example t…
-
Hi Lea, unfortunately, I cannot solve the problem without more information. Could you send me an email at ej.vankesteren@jasp-stats.org with a more detailed description of your model and your data? In general, this issue could be due to any number o…
-
Hi Ben, This is indeed currently a bug in our software. We will fix this ASAP. If you tell me the sample size of your data, I can generate a dataset for you which will create the exact results you would get with the covariance matrix. Erik-Jan
-
Hi josh, @MAgoJ is completely right! At this moment, this is not possible in JASP. In the future, we will probably enable this functionality. Keep an eye on JASP :) Erik-Jan
-
Hi Mila, the "estimate" column in the tables represent the effect estimate. For example, the total effect shows that a one point change in WoDi_DiWo_mean leads to, on average, a change of 1.005 in DiDo_DoDi_mean. The standard error is a m…