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Mplus Discussion > Structural Equation Modeling >
 Anonymous posted on Friday, April 01, 2005 - 2:35 pm

Quick question, I hope. Anyway to bootstrap the standardized factor loadings? The unstandardized are great, but we really report the standardized more often. So, I was wondering if there is any way to perform this type of test. Thanks
 Linda K. Muthen posted on Saturday, April 02, 2005 - 8:32 pm
Not at this time.
 Alexander Kapeller posted on Thursday, October 08, 2009 - 11:33 am

is it possible to get bootstrap results for the 90% confidence intervall? Thanks.

 Linda K. Muthen posted on Thursday, October 08, 2009 - 12:11 pm
No, there is no option for this.
 Alexander Kapeller posted on Saturday, October 10, 2009 - 1:26 am
Hi Linda,

in brief my task: I've a moderated mediation model with observ. var. only which has only n=46 and therefor low power. I wanted to use a 90% bcbootstrap. Can you suggest another idea? Second question: is the model result also generated by the bootstrap sample e.g. estimator for path b or only the confidence intervalls and the estimator in that section?

thanks a lot.

 Linda K. Muthen posted on Saturday, October 10, 2009 - 10:03 am
We will add 90% bootstrap in the future but for now, I have no suggestions. Only standard errors and confidence intervals are bootstrapped not parameter estimates.
 marie posted on Wednesday, October 02, 2013 - 4:32 pm

My reviewer asked me to use a bootstrapping to test my indirect effects in addition to the DELTA method. My sample size is small (140). I have missing cases so I have been using MLR in my path analysis. Bootstrapping is not available with MLR. I am using Mplus 6.2. I was wondring if it was available in the later versions or there is some other reason why the bootstrapping won't work with MLR. Is it acceptable to delete the missing values and then use ML with the bias-corrected bootstrap? The data does not seem to violate the normality assumption.


 Linda K. Muthen posted on Thursday, October 03, 2013 - 11:29 am
You can only use BOOTSTRAP wit ML and not MLR etc. because BOOTSTRAP affects the standard errors not the parameter estimates. The parameter estimates for ML, MLR, etc. are exactly the same. It is only the standard errors that differ. So use ML.
 marie posted on Saturday, October 12, 2013 - 6:29 am
Using the commands for bootstrapping in the users' guide, I got everything I wanted except for the the Standard errors of the standardized path coefficients (direct effects). All I have is a column entitled "StdYX Estimate" with the standardized path coefficients. I am asked about the effect size. I can thus provide the standardized path coefficients but no SE from the bootstrapped results. How can I ask Mplus to give me the SE for those?

 Linda K. Muthen posted on Saturday, October 12, 2013 - 9:47 am
Please send the output and your license number to
 Glenn Walters posted on Tuesday, May 13, 2014 - 4:32 am
I was wondering if it is possible to get MPlus to print out the confidence intervals to the ten thousands place. I have a lower limit of .000 and wanted to see if the value is positive or negative.
 Linda K. Muthen posted on Wednesday, May 14, 2014 - 7:53 am
You can save the results in scientific notation using the RESULTS option of the SAVEDATA command. However, it would report -.000 if it was negative. So this is positive.
 Glenn Walters posted on Wednesday, May 14, 2014 - 8:18 am
Thank you Linda. I didn't realize that MPlus used -0.000. My question has been answered.
 Ari J Elliot posted on Monday, January 05, 2015 - 6:04 pm
Hello, I have a few questions I was hoping for help with.

1. Is there any way to obtain bootstrapped confidence intervals (either bootstrap or bcboostrap) with clustered data (using TYPE=Complex)?

I have no replicate weights. I tried requesting REPSE=Bootstrap to generate the replicate weights followed by BOOTSTRAP=1000, as on p. 458 of manual, but I receive the same error message that "The BOOTSTRAP option with weights is only allowed with TYPE=COMPLEX when replicate weights are present or when REPSE=BOOTSTRAP is requested."

2. When bootstrapping is requested in ANALYSIS and CInterval, with nothing following CInterval in parentheses, in OUTPUT, are the confidence intervals bootstrapped? My understanding is that the default for CInterval is symmetric rather than bootstrapped CIs. However, p. 38 of the manual indicates that "When both the CINTERVALS and BOOTSTRAP options are used, bootstrapped confidence intervals are computed. (p. 38).

I seemed to get slightly different results when using CInterval versus CInterval(bootstrap) in conjunction with bootstrap command in ANALYSIS.

Thank you!
 Linda K. Muthen posted on Monday, January 05, 2015 - 6:25 pm
1. This is true. You would need replicate weights.

2. With BOOTSTRAP and CINTERVAL, symmetric confidence intervals using the bootstrapped standard errors are computed. The users guide is not correct in this regard.
 Ari J Elliot posted on Monday, January 05, 2015 - 6:39 pm
Thank you so much Dr. Muthen for your quick reply and for the clarification. One follow up question- can REPSE=BOOTSTRAP be used to generate replicate weights that could then be used to obtain bootstrapped SEs and CIs with clustered data? Or is this not appropriate? I confess I am not that familiar with weights in this context.
 Linda K. Muthen posted on Tuesday, January 06, 2015 - 12:00 pm
Can you send the output that shows the following message along with the data and your license number?

"The BOOTSTRAP option with weights is only allowed with TYPE=COMPLEX when replicate weights are present or when REPSE=BOOTSTRAP is requested."
 Margarita  posted on Sunday, October 09, 2016 - 9:28 am
Dear Dr. Muthen,

I have a question regarding standardised CI. I am running a 3x3 cross-lag path model:

VAR1 Time1 - VAR1 Time2, VAR1 Time3 (latents)
VAR2 Time1 - VAR2 Time2, VAR2 Time3 (latents)
VAR3 Time1 - VAR3 Time2, VAR3 Time3 (continuous)

I am using WLSMV and I also have a categorical covariate. I wanted to estimate the CI of the indirect effects and I got the following message:

BOOTSTRAP and BCBOOTSTRAP confidence intervals are only available for the regular
results of the model and MODEL INDIRECT. No confidence intervals are printed for
the standardized results of the model and MODEL INDIRECT.

I was wondering why it does not provide CI for the standardized results? I searched the manual but I couldn't find the answer. Is it because of the covariate?

Thank you in advance
 Bengt O. Muthen posted on Sunday, October 09, 2016 - 5:24 pm
It sounds like you are not using version 7.4.
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