Very educational and still very high-level. Is there guiding videos/screencasts on meta-analysis with different types of response variables, modulators and outcomes? Perhaps covering the considerations of multivariate and multilevel meta-analysis as well as composite outcome meta-analyses, such as the concept of "borrowing of strength" (BoS) in meta-analysis where one has to deal with multiple outcomes (response variables) or studies with small sample sizes. Thank you

Thank you for this insightful exposition to mirt. I am currently on an academic thesis at the University of Nigeria, Nsukka to study the DIF if a state examination, using many methods of which mirt is one. I find this video very instructive and followed through until I couldn't view the script you engaged to perform DIF. Could you share the script with me, or guide me to write my own script uniquely? Here is my unique case: I coded a 41-column dichotomously scored dataset with the name ESUPE _G.csv with the first column named gender as the grouping variable. In my data columns 2 to 40 are the item responses, while column 1 holds the gender grouping. I intend to run a DIF analysis using mirt package in R. How do I write a good R-script for the DIF analysis to flag DIF items? Thanks

One of the most useful videos that exists on the internet. Thank you for this.

❤

Thank you very much for the video, it is very helpful! I am glad I have a chance to ask you a question here about it as well! I have the following problem. It happened that I have only one level-2 variable and it has several missing values(it was an online survey from two organizations and there was a trouble with the data collection, so I am am sure the missing data is MCAR). I try to use 2lonly.pmm to fill in the gaps. I specify this variable as a -2 in pred: suppressWarnings(suppressMessages( ini <- mice(df, maxit = 0) )) pred <- ini$pred pred [,"school"] <- -2 When running the mice function it gives me the following error: Error in check.cluster(data, predictorMatrix) : Convert cluster variable school to integer by as.integer() I switched the organization variable to an integer and the error message then became as the following: Error in .imputation.level2(y = y, ry = ry, x = x, type = type, wy = wy, : No class variable I added additional variable "city", where both organizations are at, and specified it as a cluster variable in the pred. It didn't help, same error. Then I tried to specify the full pred matrix in excel and read it from a csv file as a matrix, the error changed to: Error in predictorMatrix[h, ] : subgroup out of bounds I consulted your book again and saw the following passage: "It is conceptually straightforward to extend imputations to higher levels (Yucel 2008). If there are two levels, combine all level-2 predictors with an aggregate (e.g., the cluster means) of the level-1 predictors and the level-1 outcomes. Once we have this, we may choose suitable methods from Chapter 3 to impute the missing level-2 variables in the usual way. No new issues arise." Is there a way to fix my problem? Or, given the above, is there maybe a way to not treat this variable as a cluster variable and just impute it with logreg in mice since it's the only one variable? Do you mean by aggregate to compute mean values or cluster variables? Thank you in advance for reading the post and have a great day ahead! Best Regards, Yulia

definitely a step in the right direction that can't come by chance from a neuroscientist like you , thank you very much

The best introduction to SEM I''ve seen. Thanks.

Thank you very much, very insightful lesson. Could you please tell me where I can also find a lesson or some material on meta-analysis of survival data (Hazard Ratios). It would really help. Thanks

Just what I have been looking for !. Thanks a lot.

What a great and insightful talk! Thanks a lot🎉

Hi. My first question for MetaSem: do the correlation coefficients have to be given in the primary studies? For example, can't MetaSem be done using d or g effect sizes? My other question is what exactly is the difference between MetaSem and meta-analysis? Thank you very much in advance for your answers...

Hello, Author. Could you tell me how to get the residual vairances of a MSE by lavaan()? Thanks

What about plotting posterior distributions and seeing how well they mirror the observed distribution (ie the PPE check)? Similarly, plotting predicted vs observed scatterplots, like in Shinystan for HLM models? Ty :)

can you just show me how to open metasem in R studio

keep up the good work mate!

Thank you!:)

Really fascinating video, please share me if you have a video lecture on the continuous data meta analysis for ecological study

Thank you for such a great video.

Thank you for the package, is very helpful.

It's a great great course. Thank you!

Thanks a lot for this great presentation. It is very informative.

Thank you very much to all presenters! This is a very newbie-friendly video to learn SEM using R! Everything is well organized and well explained! Looking for more good videos:)

Teaching this to my class thanks to this. Much thanks!

thank you so much for this video and other lectures of this channel!!!

Please more. Explanation of item caractéristique curve in rash model

Thank you for this video! Do you have any advice on how to organzie data when doing the extracting from studies? Do you use excel or something? I want to do a meta analysis on low birth weight and mental health, but there are sooo many different tests for mental health that I cant think out a smart way to organize it in excel.

Why we need to use absolute latitude? Can I change to other variables?

Thank you, What's Ablat? How could I get Ablat?

Thank you for the package! It's pretty good! I'm wondering, if you have a citeable source for thresholds of epsilon²? I need to interpret the effect size but can not find any source for thresholds or a rule of thumb for the interpretation... Any help is appreciated.

Thank you so much for the video. It helped me a lot to understand and interpret the results of blavaan!

Amazing package. Thank you! I'm wondering how to model the covariance structure in a bayesian longitudinal setting, similar to covariance patterns such as compound symmetry, autoregressive, Topelitz etc. in the frequentist world. In the frequentist world, taking serial correlation into consideration narrows the confidence intervals of the parameters. How to model the covariance structure in a bayesian longitudinal setting? I'm wondering if a bayesian intercept always introduces compound symmetry, similar to a random intercept in a frequentist linear mixed effects model? I suspect taking serial correlation would narrow the posterior distributions of the model parameters, strengthening the bayesian inference. However, I'm not at all sure if my thoughts are anywhere near correct. The brms package is a very valuable resource. However, the parts about covariance structures seem to be still in progress. If anyone has good theoretical (and why not practical) bayesian references regarding these covariance modeling issues (serial correlation etc.), I would appreciate them very much.

Thank you so so so much for this AMAZING tutorial!!! This is actually my second time trying to use R, and this video was a huge help in understanding the basic logic behind conducting SEM using R. I could even code the mediation model by myself in 3 minutes, which made me very happy :D You are a great educator

Thank you for your service to the descipline of evidence synthesis.

Many thanks for developing a package lile this

The caretList function doesn't seem to exist.

Thank you, great work and it helps a lot, inspires me to apply the method in my research works.

Are you able to extract model fit values, such as AIC and log-likelihood, after applying the coef_test function? Thanks.

Definitely one of the best videos about machine learning. It was quite informative and the narration was smooth. Thank you very much 😃

So insightful and applicable. Many thanks. Also would be very grateful if you could provide such videos for Network Meta-Analysis. Thanks.

30:27 Intro 34:38 Speakers Talk

How to change the font style of part of a string in forestplot? Specifically, I want to italicize the text (ABCX (rs1111111-X)), which is the name of one of the columns.

Is it possible to forest plot odds ratios when only given the ratio and upper and lower limits? Since many studies plainly list their OR with 95%CI and p value without reporting the samples sizes. I cannot seem to find any videos regarding this and would greatly appreciate some advice.

Wonderful package and very simple syntax...

Thank you for this useful video! Can you please talk about experimental meta-analysis using R

Hi, I am struggling to run a metanalysis. It is my first time. I have continuous data with mean, sample size, and standard deviation for each study (without means for control and exposure groups.) Any ideas on the appropriate argument suitable for this type of data?

Wonderful presentation! Thank you so much! :)

Very useful, good video!

Thank you

Really great meetup, a little question here, why do we need RVE when the multilevel model is already designed for dependent effect sizes at a certain level?

Very useful tutorial, thanks you!!