Univariate Binary Model with multiple covariates that are binary, categorical, and continuous.
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Rolandgem
Joined: 10/24/2015
| Attachment | Size |
|---|---|
| univariateThreshold.R | 4.8 KB |
| data.csv | 705 bytes |
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This is my first attempt at binary univariate models with multiple covariates. When i fit the saturated model I get the following error which I am not sure what it actually means:
Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
MxComputeConfidenceInterval: reference fit is not finite
My guess is that it has something to do with the values or bounds?
What are some guidelines for choosing values when you have binary variables (as well as a mix of binary and continuous covariates)?
I have attached the code and a sample of my data. Since this is my first attempt at modelling twins I would greatly appreciate any comments regarding the format of my data and feedback regarding my code.
Thanks :)
MxComputeConfidenceInterval: reference fit is not finite
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In reply to MxComputeConfidenceInterval: reference fit is not finite by jpritikin
I did as you suggested. So
> # 1) RUN Saturated Model
>
> SatFit <- mxRun(SatModel, intervals=FALSE)
Running Sat with 10 parameters
Warning message:
In model 'Sat' Optimizer returned a non-zero status code 10. Starting values are not feasible. Consider mxTryHard()
> (SatSumm <- summary(SatFit))
Summary of Sat
Starting values are not feasible. Consider mxTryHard()
free parameters:
name matrix row col Estimate lbound ubound
1 BaTH MZ.BageTH 1 1 0.1
2 BsTH MZ.BsexTH 1 1 0.1
3 BpTH MZ.BphuTH 1 1 0.1
4 BparTH MZ.BpartTH 1 1 0.1
5 Tmz11 MZ.ThMZ 1 1 0.8 -2 2
6 imz11 MZ.ThMZ 1 2 1.0 0.001 2
7 MZ.expCorMZ[1,2] MZ.expCorMZ ebent1 ebent2 0.6 -0.99 0.99
8 Tdz11 DZ.ThDZ 1 1 0.8 -2 2
9 idz11 DZ.ThDZ 1 2 1.0 0.001 2
10 DZ.expCorDZ[1,2] DZ.expCorDZ ebent1 ebent2 0.3 -0.99 0.99
observed statistics: 16568
estimated parameters: 10
degrees of freedom: 16558
fit value ( -2lnL units ): Inf
number of observations: 8284
Information Criteria:
| df Penalty | Parameters Penalty | Sample-Size Adjusted
AIC: Inf Inf NA
BIC: Inf Inf Inf
CFI: NA
TLI: 1 (also known as NNFI)
RMSEA: 0 [95% CI (NA, NA)]
Prob(RMSEA <= 0.05): NA
OpenMx does not recommend using GFI, AGFI, NFI (aka Bentler-Bonett), or SRMR:
See help(mxSummary) for why.
Some of your fit indices are missing.
To get them, fit saturated and independence models, and include them with
summary(yourModel, refModels=...)
See help(mxRefModels) for an easy way of doing this in many cases.
timestamp: 2015-10-28 17:36:25
Wall clock time (HH:MM:SS.hh): 00:00:00.64
optimizer: SLSQP
OpenMx version number: 2.3.1
Need help? See help(mxSummary)
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In reply to I did as you suggested. So by Rolandgem
starting values
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In reply to I did as you suggested. So by Rolandgem
Starting values ok I think
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In reply to Starting values ok I think by AdminNeale
I tried to use the sex and
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In reply to I tried to use the sex and by Rolandgem
I think the crash is because of something else
Could you say more about the crash you encountered? It's always possible it's due to a bug, and even if it isn't, we can help you troubleshoot.
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In reply to I think the crash is because of something else by AdminRobK
Factor as a definition variable
I have two projects where I would like to use ordinal or categorical variables as covariates.
In the simple case, the there is one covariate (5 non-ordered categories). Another model includes age (continuous), sex (I understand 0-1 coding is fine here), and two non-ordered categorical variables.
My search keep leading me to this thread.. any updates?
Thanks!
Brooke
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In reply to Factor as a definition variable by bhuibregtse
dummy coding, etc.
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