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| Missing data and case deletion |
 
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| Lydia posted on Friday, September 27, 2013 - 2:00 pm
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I am new to MPlus and have what probably is a basic question but I can't seem to get a clear answer.
I am doing an EFA using the default ML estimation. I got this warning:
Data set contains cases with missing on all variables. These cases were not included in the analysis. Number of cases with missing on all variables: 52
Is there any other missing data estimation method that would allow me to use those 52 in anyway? imputation?
Thank you. |
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| No. When a case has nothing to contirubute, it cannot be used with FIML or multiple imputation. |
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| Andrea S posted on Wednesday, November 20, 2013 - 10:36 pm
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Hi Dr Muthen(s)
Im conducting linear growth modeling of my DV (lem) with a time-varying covariate (lse), with data over three time periods (equal time points). Im using version 6 of the software, and my understanding of the defaults of this version is that listwise deletion is off unless specifed, and that the default with missing data should be to use all available data. However, according to the output, I believe the analsyes are only using the data in which participants have data on at least 5/6 measures (lem1-3, and lse1-3), rather than using all available data. This is reducing my sample size significantly. Is there any way to get around this/am I doing anything wrong?
Syntax below:
missing are all (-999);
USEVARIABLES ARE lem1 lem2 lem3 lse1 lse2 lse3;
analysis: type = random;
Estimator = ML;
MODEL:
i s | lem1@0 lem2@1 lem3@2;
lem1 ON lse1;
lem2 ON lse2;
lem3 ON lse3;
Many thanks in advance for your time,
Andrea |
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| You can change the value 0f the time-varying covariates for those observations that have missing on the dependent variable to any number other than the missing value flag. Then those cases will not be eliminated from the analysis. |
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