metaSEM
http://openmx.psyc.virginia.edu/taxonomy/term/44/0
enThis forum is about the metaSEM package for meta-analysis
http://openmx.psyc.virginia.edu/thread/2946
<p><a href="http://courses.nus.edu.sg/course/psycwlm/internet">Mike Cheung's</a> metaSEM package is introduced <a href="http://courses.nus.edu.sg/course/psycwlm/Internet/metaSEM">here</a></p>
<p>Post questions to this forum</p>
http://openmx.psyc.virginia.edu/thread/2946#commentsmetaSEMSat, 26 Apr 2014 21:26:16 +0000tbates2946 at http://openmx.psyc.virginia.eduInstalling metaSEM
http://openmx.psyc.virginia.edu/thread/3897
<p>Dear Mike,</p>
<p> I'm having some problems for installing metaSEM package...This error always appears, and I cannot find the solution:</p>
<p>install.packages("metaSEM")<br />
Installing package into ‘D:/Documents/R/win-library/3.0’<br />
(as ‘lib’ is unspecified)<br />
Warning in install.packages :<br />
package ‘metaSEM’ is not available (for R version 3.0.2)</p>
<p>Where could I find a new version of the package?</p>
<p>Thanks in advantage,</p>
<p>Kind regards.</p>
http://openmx.psyc.virginia.edu/thread/3897#commentsmetaSEMThu, 11 Sep 2014 17:27:57 +0000Bfcastilla3897 at http://openmx.psyc.virginia.eduEquality Constraints
http://openmx.psyc.virginia.edu/thread/3606
<p>Hi Mike,</p>
<p>In my stage two analysis I would like to impose equality constraints on some items' error variances in the S matrix to be consistent with the models from the original studies. </p>
<p>I wonder whether this is feasible at all, because here (<a href="http://courses.nus.edu.sg/course/psycwlm/Internet/metaSEM/masem.html" title="http://courses.nus.edu.sg/course/psycwlm/Internet/metaSEM/masem.html">http://courses.nus.edu.sg/course/psycwlm/Internet/metaSEM/masem.html</a>) you wrote "Since we are conducting a correlation structure analysis, the error variances are not free parameters."</p>
<p>If it is possible, could you please provide a syntax example how to implement the equality constraints? </p>
<p>Many thanks for your help!<br />
Johannes</p>
http://openmx.psyc.virginia.edu/thread/3606#commentsmetaSEMThu, 03 Jul 2014 11:41:19 +0000jbauer3606 at http://openmx.psyc.virginia.eduBayesian MASEM
http://openmx.psyc.virginia.edu/thread/3439
<p>Dear Mike</p>
<p> I remembered you mentioned about Bayesian approach to MASEM in discussion part of your article.<br />
I think this topic is very intriguing to me and to unknown others. Could you detail more about the issue here?<br />
If you don't mine, I hope you to recommend some direct reference on this issue.<br />
Personally I ask questions as follows,<br />
what might be advantages of Bayesian approach in comparison to TSSEM or GLS?<br />
In Bayesian, is WLS replaced by Bayesian process? or just modified by it? or other than the replacement?<br />
Can I understand Bayesian approach into MASEM on the basis of typical Bayesian SEM?<br />
What might be difference that should be borne in mind?</p>
<p> Sorry for being too discursive.<br />
Excuse me, I just want to know more about Bayesian MASEM particularly.<br />
and I consider it as a worthy question hopefully.<br />
I look forward to your response. </p>
http://openmx.psyc.virginia.edu/thread/3439#commentsmetaSEMWed, 25 Jun 2014 15:08:33 +0000James Lee3439 at http://openmx.psyc.virginia.edutssem2 over a given pooled correlation matrix
http://openmx.psyc.virginia.edu/thread/3410
<p>Hi again Mike, </p>
<p>I was wondering if this is possible:<br />
Having the pooled correlation matrix and their standard errors, do you have any way to apply directly the second stage of tssem over that data? Any help would be very much appreciated. </p>
<p>Thanks a lot, </p>
<p>Laura</p>
http://openmx.psyc.virginia.edu/thread/3410#commentsmetaSEMWed, 25 Jun 2014 00:07:25 +00003410 at http://openmx.psyc.virginia.eduNot positive definite matrix
http://openmx.psyc.virginia.edu/thread/3409
<p>Hi Mike,</p>
<p>I'm making a lot of progress with the package but I still have some questions.<br />
When I try to run the tssem1 I get some non-positive definite matrix.<br />
I think it is because the determinant is lower than 0. Do you have implemented partial least square or ridge to resolve this problem?</p>
<p>Thank you in advantage,</p>
<p>Laura</p>
http://openmx.psyc.virginia.edu/thread/3409#commentsmetaSEMTue, 24 Jun 2014 23:58:16 +00003409 at http://openmx.psyc.virginia.edunot positive definite and NA errors
http://openmx.psyc.virginia.edu/thread/3408
<p>Hi Mike, </p>
<p>I am currently trying to fit a multivariate metaSEM model. I am getting a non-positive definite matrix when fitting a random effects model, and this is likely expected due to a lot missing data in the attached datafile. Would you agree that this is the reason behind the non-positive definite error? Please also note that I tried running the model with fewer studies that provided more data (the number of studies went from 108 to 44) but the errors were the same. </p>
<p>Additionally, I can’t seem to fit the fixed effects model. Given that I am new to R, I was hoping you could look at my code below and let me know how you have handled “NA” or missing values in metaSEM. Below is all the code I have used, as well as the errors. </p>
<p>Thanks in advance, </p>
<p>Yusra</p>
<p>#importing the dataset with a matrix for each sample<br />
my.full <- readFullMat("T:/matrix.dat")</p>
<p>#creating an object with the sample sizes<br />
n <- ("100 100 100 100 100 100 241 45 70 122 119 119 447 56 41 38 103 57 192 105 62 48 56 123 56 123 121 103 300 128 106 20 17 75 10 19 21 492 153 107 71 123 23 15 14 22 131 727 30 297 60 125 37 140 88 182 735 45 300 300 77 136 162 65 166 60 75 87 59 57 97 129 242 83 54 78 75 30 60 105 65 64 92 101 120 88 144 120 464 104 296 120 121 95 76 60 256 251 317 52 622 80 297 171 98 354 690 88")</p>
<p>#random effects model<br />
> random.full <- tssem1(my.full, n, method = "REM", RE.type="Symm", RE.startvalues=0.1, RE.lbound=1e-10, I2="I2q", model.name=NULL,suppressWarnings=TRUE)<br />
Error in function (x, n, cor.analysis = TRUE, dropNA = FALSE, as.matrix = TRUE, :<br />
x is not positive definite!</p>
<p>#fixed effects model<br />
> fixed1 <- tssem1(my.full$data, n$n, method = "FEM", cor.analysis = TRUE, cluster = NULL, RE.type= "Symm", suppressWarnings=FALSE)<br />
Error in !all.equal(my.range[1], my.range[2]) : invalid argument type<br />
In addition: Warning messages:<br />
1: In min(x, na.rm = na.rm) :<br />
no non-missing arguments to min; returning Inf<br />
2: In max(x, na.rm = na.rm) :<br />
no non-missing arguments to max; returning -Inf</p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/matrix.dat">matrix.dat</a></td><td>62.18 KB</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/3408#commentsmetaSEMTue, 24 Jun 2014 15:32:00 +0000yahmed3408 at http://openmx.psyc.virginia.eduError running REM in tssem1
http://openmx.psyc.virginia.edu/thread/3384
<p>Hi Mike,<br />
I am enjoying so much your package MetaSEM, thanks a lot! This is making a great advance in meta-analysis.<br />
I am having a bit of problem running random effects with tseem1, any help would be very much appreciated!<br />
I am trying to replicate Digman97 using a larger sample, here an example of a reduced sample of my data and the error I got.<br />
> random1 <- tssem1(neo$data, neo$n, method="REM", RE.type="Diag")<br />
Error: The reference '21' in mxMatrix("Stand", nrow = p, ncol = p, free = TRUE, values = jitter(vechs(cov2cor(x.new))), name = "S", labels = acovName) is illegal because it can be interpreted as a number</p>
<p>Am I missing anything?<br />
Thanks in advanced!<br />
Laura.</p>
<p>[img_assist|nid=3383|title=Error running REM in tssem1|desc=|link=none|align=left|width=100|height=50]</p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/ex.xls">ex.xls</a></td><td>84 KB</td> </tr>
<tr class="even"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/neo.R">neo.R</a></td><td>803 bytes</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/3384#commentsmetaSEMMon, 23 Jun 2014 22:21:14 +00003384 at http://openmx.psyc.virginia.edudifference between corrected input and raw input
http://openmx.psyc.virginia.edu/thread/3051
<p> Dear professor Mike</p>
<p> I remember that you seem to mention from one of your article that a performance of MASEM model with and without artifact correction is worthy of scholarly attention.<br />
Am I right? By the way, It has been the topic i am always wondering about since i read your article.<br />
Corrected correlation might actually cause systematic bias, to some degree, compared to raw correlation.<br />
However, this bias has nothing to do with performance maybe because it is more likely to do with estimation method and sample sizes.</p>
<p> Performance Comparison between two model is feasible? then, what can be absolute criteria for that?<br />
I would like to ask your opinion on that issue.</p>
http://openmx.psyc.virginia.edu/thread/3051#commentsmetaSEMThu, 15 May 2014 14:31:46 +0000James Lee3051 at http://openmx.psyc.virginia.eduWhere to go from here?
http://openmx.psyc.virginia.edu/thread/3034
<p>Hi Mike,</p>
<p>All of your posts have been extremely helpful. However, I do have a few remaining questions.</p>
<p>I read that it is easier to download the OpenMX and metaSEM packages in RStudio, so that's what I did and I think it worked. I just don't know how to test it - do you have any sample data sets that I could plug into a session to see if it works?</p>
<p>Also, do you recommend sticking with R instead of RStudio? We will be using it for an extensive project and don't want to run into problems down the line if RStudio doesn't work as well as R.</p>
<p>Thanks so much!</p>
<p>Virginia</p>
http://openmx.psyc.virginia.edu/thread/3034#commentsmetaSEMTue, 13 May 2014 13:28:42 +0000vmccaughey3034 at http://openmx.psyc.virginia.eduInstallation Prevention Error
http://openmx.psyc.virginia.edu/thread/3005
<p>Hello!</p>
<p>I am very new to this software. After installing R (version 3.1.0), I have copy pasted each code to install metaSEM. However, after installing OpenMX, ellipse, and mass packages, when it is time to install the metaSEM package, I keep recieving the same error. I have attached an image with the error code. Has anyone else had this problem / know how to help? </p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/metaSEMerror.png">metaSEMerror.png</a></td><td>185.1 KB</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/3005#commentsmetaSEMFri, 09 May 2014 20:53:45 +0000alainabaker3005 at http://openmx.psyc.virginia.eduTwo errors at Stage 1
http://openmx.psyc.virginia.edu/thread/2960
<p>Hi all,</p>
<p>Thank you for this wonderful software and very useful forum for running metaSEM. I'm new to both R and metaSEM, but I've generally found it to be relatively straightforward with all the great resources available.</p>
<p>There are a pair of metaSEM models I'm running that have been giving me two separate error messages that I can't wrap my head around. These occur when running the Stage 1 portion of the script:</p>
<p>1. Error: The observed covariance matrix is not a symmetric matrix<br />
(This seems akin to problems described here [http://openmx.psyc.virginia.edu/thread/1039] where values estimated at, say, the 16th decimal point end up being slightly different above/below the diagonal. The fix seems to simply be to round numbers, but I'm not sure how to access the guts of the metaSEM package to do this).</p>
<p>2. Error in lambda[length(lambda)]/lambda[1] > tol :<br />
invalid comparison with complex values<br />
(I'm not sure what this means).</p>
<p>Also, just to be clear, I don't receive both of these messages at the same input matrices but rather on separate metaSEMs I'm running. Any ideas? Thanks!</p>
<p>--B</p>
http://openmx.psyc.virginia.edu/thread/2960#commentsmetaSEMTue, 29 Apr 2014 11:59:55 +0000Brian S Connelly2960 at http://openmx.psyc.virginia.eduIndividual participant data
http://openmx.psyc.virginia.edu/thread/2877
<p>Hello Mike,</p>
<p>in your 2014 article on MASEM (Behav Res, DOI 10.3758/s13428-013-0361-y) you mention individual participant data (IPD) meta-analysis as a tool for addressing issues in MASEM, such as categorical response variables. I am wondering what would be an advisable analytic strategy for MASEM with IPD (assuming a fixed effects model). </p>
<p>Here are several options I found:<br />
(1) One approach could be to extract a correlation matrix from each study and analyze it with TSSEM in metaSEM.<br />
(2) Cooper and Patall (2009, Psych. Methods) mention that study can be used as a stratification variable.<br />
(3) Curran and Hussong (2009, Psych. Methods) suggest including study membership as a categorical predictor as well as its interactions with other predictors in the model. </p>
<p>From my perspective, approach 1 is straightforward, but I am not sure whether it is applicable to my specific case (models based on categorical items, cluster sampling). Approach 2 is straightforward to implement, e.g. in Mplus, but I am not sure about its drawbacks. It just seems too easy. Approach 3 seems impractical with complex SEMs because including several latent/observed interactions quickly leads to overcomplex models and estimation problems. </p>
<p>What would be the best choice?</p>
<p>Many thanks<br />
Johannes</p>
http://openmx.psyc.virginia.edu/thread/2877#commentsmetaSEMTue, 15 Apr 2014 09:41:54 +0000jbauer2877 at http://openmx.psyc.virginia.eduEffects from TSSEM larger than in original studies
http://openmx.psyc.virginia.edu/thread/2872
<p>Hi Mike, </p>
<p>many thanks for the fantastic metaSEM package! I used it to combine models from two original studies. </p>
<p>(1) What astonishes me is that some of the structural parameters estimates from TSSEM Stage 2 are even larger than the ones from the individual studies (e.g. study 1: beta = -.40; study two: beta = -.53; TSSEM2: beta = -.66). Naively I had expected that the comnbined TSSEM2 etimates should be somewhere between the ones of the original studies. I am wondering how this is possible. Can I trust this finding? </p>
<p>(2) Since my model contains two mediation paths: Is it possible to get LB confidence intervals for indirect effects?</p>
<p>Many thanks<br />
Johannes</p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/output_1.txt">output.txt</a></td><td>37.29 KB</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/2872#commentsmetaSEMTue, 15 Apr 2014 08:01:33 +0000jbauer2872 at http://openmx.psyc.virginia.eduaccumulative sample size
http://openmx.psyc.virginia.edu/thread/2861
<p>Dear Mike,</p>
<p>Is there an approach to compute the accumulative sample size (N)? </p>
<p>It is quite convenient to know the number of primary studies (n) by "pattern.na ( )", but I can't find a syntax for the accumulative sample size (N).</p>
<p>Thanks in advance!</p>
<p>Ryan</p>
http://openmx.psyc.virginia.edu/thread/2861#commentsmetaSEMMon, 14 Apr 2014 07:46:09 +0000Ryan2861 at http://openmx.psyc.virginia.edu