Kucharssim
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Dear @Doris, I am not aware of SPSS using different calculations, but it is possible. JASP uses calculations provided by the ppcor package for R: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681537/ If you'd like, you can share your data with us s…
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Hi @MaBH, The AVE is calculated by the package semTools, from its documentation (https://search.r-project.org/CRAN/refmans/semTools/html/AVE.html) we can read that the AVE is calculated as https://forum.cogsci.nl/uploads/416/R8PISI52IRIS.png Now I d…
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Hi @Adhamragab, The arrows on the right represent the residual/error variance. The thicker the arrow, the more variance of the variable is left unexplained by the latent factors. Cheers, Simon
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Dear @derya, I am not sure what you mean by 'the syntax', but I am assuming you want the lavaan model specification with the group constraints? Please correct me if I am wrong. The CFA analysis in JASP does not use the lavaan model syntax to specify…
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Dear @ravigarg415, it is indeed not possible in the current JASP version. However, we recently implemented multinomial, ordinal, and Firth logistic regressions as new options in the GLM analysis. This will be available in the next JASP release which…
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Dear Fatima, Thank you for your question. Currently it is not possible to change the cut-off for the logistic regression. I made a feature request on our GitHub page (https://github.com/jasp-stats/jasp-issues/issues/1939). Please check for new devel…
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Dear @Mike_Szymczuk, thank you for your question. These cutoffs are based on the probability scale, so for instance 0.8 cut-off means that if a data point is predicted to have at least 80% probability of being in the "positive" category, …
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Dear @mmm, The data library contains a "Dancing Cats and Dogs" file that reanalyses this example from Andy Field's popular statistical textbook, and shows how to conduct a log-linear regression in JASP. Unfortunately, we do not have any ot…
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Dear @KiBe, unfortunately, the CFA analysis is limited to only one model per analysis, so it is not possible to directly compare multiple models to each other (apart from manually compare the fit statistics) within the analysis. However, you can use…
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As E.J. points out, "Tenure" is highly significant. Since you have only one predictor in the model, you can also see this in the model summary table where the model that includes "Tenure" outperforms the null model. The pseudo R-…
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Sorry for the tardy response! It seems there is a bug, I filed an issue on GitHub so that we can keep track of it better: https://github.com/jasp-stats/jasp-issues/issues/1687
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Dear @sethakap, As far as I can tell, I cannot compare models using by adding model 2, etc (as any change I make to one model seems to replicate in the other models. . . instead of being independent from the other models). That is indeed strange! It…
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Hello, Categorical variables in SEM are tricky, and it really depends on your data and hypotheses you want to test. In case that the levels in the variable can be ordered, then it is possible to conduct the analysis as if it was a continuous variabl…
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Hello @MBD, you can obtain the p-values and other information (such as confidence intervals) using the output tables (you should automatically obtain a section "Parameter estimates" with tables of direct and indirect effects, total and tot…
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the bootstrapping is not done in the sem function because it is done a couple of lines later, calling the lavBootstrap function (https://github.com/jasp-stats/jaspSem/blob/2e91f22bff99e849258b0bee51de3c764abf2e34/R/common.R#L26) so that JASP can dis…
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No worries! Yes, you are right - the difference in your example is caused by the missing values. By default, JASP uses Full Information Maximum Likelihood to deal with missing values. If you want to make the results in R the same as in the JASP fil…
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Dear Charlotte, attached are files that show you how to reproduce results from JASP in R. I can help you get to the bottom of your specific example if you are willing to share your data and your JASP file. Best, Simon https://forum.cogsci.nl/upload…
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Dear @mani, the colors should indeed correspond to the values of the correlation coefficient (red for negative, blue for positive correlations). Your observation that some correlations are labeled as -1 but with no color suggests that there might be…
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Dear @may01dz, it is currently not possible in the module, but it is on the to-do list!
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Dear @mani, I would like to ask more details about your use case. It seems to me you have multiple predictors, in that case, the binary classification alone will not help you there. I have some scenarios in mind, please let me know if I am misunders…
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Just to follow up: it is actually not a bug in the analysis, I was looking at a wrong column. The solution is to open the Advanced tab in CFA and select a standardization. To get the same coefficients as in the standardized model plot, select Standa…
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Dear mgupta, the option to standardize the parameter estimates in CFA is under Advanced -> Standardization. However, I see that switching the standardization method does not change anything in the table, which seems like a bug in JASP. I will ins…
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Dear Brunofd, The "estimator" and "error calculation" options in the SEM analysis correspond to options "estimator" and "se" arguments in lavaan. So selecting Robust DWLS in JASP should give you the same resul…
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Hello everyone, the Release constraints box should accept the same syntax as the group.partial argument in lavaan. See https://lavaan.ugent.be/tutorial/groups.html, section "Constraining groups of parameters to be equal across groups" for …
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Dear Nathalie, we are working on an alternative method, but it’s not currently implemented in any software and we need to tidy up some proofs. The new method is relatively straightforward to conduct though (some materials are here https://osf.io/xv2…
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Hello, As E.J. says, "condition on" is used to compute a partial correlation - whatever is put in this box is used as the "conditioning"/"controlling" variables. I am not sure whether this is appropriate for your data,…