Is there a way to set the precision of the reported p values to more than 2 decimal places. It might be something simple, but I can't find it in the documentation.

I can reproduce the above when pasting the code you gave, but in my own models I get NA for Summary and 2 decimal places in the tableFitStatistics function:

observed statistics: 1006
Constraint 'MeanMZFt1_t2' contributes 1 observed statistic.
Constraint 'MeanMZMt1_t2' contributes 1 observed statistic.
Constraint 'MeanDZFt1_t2' contributes 1 observed statistic.
Constraint 'MeanDZMt1_t2' contributes 1 observed statistic.
estimated parameters: 39
degrees of freedom: 967
-2 log likelihood: 1195.697
saturated -2 log likelihood: NA
number of observations: 1124
chi-square: NA
p: NA
AIC (Mx): -738.3029
BIC (Mx): -2798.569
adjusted BIC:
RMSEA: NA
timestamp: 2010-11-12 12:51:48
frontend time: 8.36237 secs
backend time: 9.81115 secs
independent submodels time: 8.487701e-05 secs
wall clock time: 18.17360 secs
cpu time: 18.17360 secs
openmx version number: 1.0.3-1505

tableFitStatistics is not part of OpenMx, but of a set of helper functions. it has not precision parameter. You could look inside and alter how it works if you want/can.

Alternatively, you might try the built in model comparison function

Where are you seeing p-values with two decimal places?

Summary gives 7 for most values: p: 0.1936117

require(OpenMx)

data(demoOneFactor)

manifests <- names(demoOneFactor)

latents <- c("G")

factorModel <- mxModel("One Factor",

type="RAM",

manifestVars = manifests,

latentVars = latents,

mxPath(from=latents, to=manifests),

mxPath(from=manifests, arrows=2),

mxPath(from=latents, arrows=2,

free=FALSE, values=1.0),

mxData(cov(demoOneFactor), type="cov",

numObs=500))

summary(mxRun(factorModel))

Hi Tim,

What am I doing wrong?

I can reproduce the above when pasting the code you gave, but in my own models I get NA for Summary and 2 decimal places in the tableFitStatistics function:

observed statistics: 1006

Constraint 'MeanMZFt1_t2' contributes 1 observed statistic.

Constraint 'MeanMZMt1_t2' contributes 1 observed statistic.

Constraint 'MeanDZFt1_t2' contributes 1 observed statistic.

Constraint 'MeanDZMt1_t2' contributes 1 observed statistic.

estimated parameters: 39

degrees of freedom: 967

-2 log likelihood: 1195.697

saturated -2 log likelihood: NA

number of observations: 1124

chi-square: NA

p: NA

AIC (Mx): -738.3029

BIC (Mx): -2798.569

adjusted BIC:

RMSEA: NA

timestamp: 2010-11-12 12:51:48

frontend time: 8.36237 secs

backend time: 9.81115 secs

independent submodels time: 8.487701e-05 secs

wall clock time: 18.17360 secs

cpu time: 18.17360 secs

openmx version number: 1.0.3-1505

> expectedMeansCovariances(equateMeansTwinFit)

...

> tableFitStatistics(univTwinSatFit, equateMeansTwinFit)

Name ep -2LL df AIC diffLL diffdf p

Model 1 : univTwinSat 39 1184.36 963 -741.64 - - -

Model 2 : equateMeansTwin 39 1195.7 967 -738.3 11.33 4 0.02

Thanks

tableFitStatistics is not part of OpenMx, but of a set of helper functions. it has not precision parameter. You could look inside and alter how it works if you want/can.

Alternatively, you might try the built in model comparison function

mxCompare(model1,model2)

Thanks Tim,

I wasn't even aware about mxCompare.

Also note from the mxCompare help file:

"Use options(‘digits’=N) to set the minimum number of significant digits to be printed in values."