Hello,
It appears that the argument bq in mxBootstrapEvalByName() function does not accept new probabilities and only computes the default probabilities. To show, I am pasting below a self-contained example and its output:
library(OpenMx) data(multiData1) manifests <- c("x1", "x2", "y") biRegModelRaw <- mxModel( "Regression of y on x1 and x2", type="RAM", manifestVars=manifests, mxPath(from=c("x1","x2"), to="y", arrows=1, free=TRUE, values=.2, labels=c("b1", "b2")), mxPath(from=manifests, arrows=2, free=TRUE, values=.8, labels=c("VarX1", "VarX2", "VarE")), mxPath(from="x1", to="x2", arrows=2, free=TRUE, values=.2, labels=c("CovX1X2")), mxPath(from="one", to=manifests, arrows=1, free=TRUE, values=.1, labels=c("MeanX1", "MeanX2", "MeanY")), mxAlgebra(b1-b2, name = "diff"), mxData(observed=multiData1, type="raw")) biRegModelRawOut <- mxRun(biRegModelRaw) boot <- mxBootstrap(biRegModelRawOut) summary(boot, boot.quantile=c(.025,.975)) mxBootstrapEval(b1-b2, boot , bq= c(.025,.975) ) ### The argument bq does not have an effect mxBootstrapEvalByName("diff", boot , bq= c(.025,.975) )
Here is the output:
Show in New WindowClear OutputExpand/Collapse Output Running Regression of y on x1 and x2 with 9 parameters Running Regression of y on x1 and x2 with 9 parameters Summary of Regression of y on x1 and x2 free parameters: name matrix row col Estimate Std.Error 2.5% 97.5% 1 b1 A y x1 0.4479124 0.04182010 0.3680974 0.5320819 2 b2 A y x2 0.4327148 0.03555289 0.3678668 0.5031941 3 VarX1 S x1 x1 1.1364299 0.05221950 1.0330193 1.2347567 4 CovX1X2 S x1 x2 0.5811058 0.04784627 0.4802935 0.6586185 5 VarX2 S x2 x2 1.5556045 0.07247085 1.3744765 1.6734908 6 VarE S y y 1.4119922 0.06697778 1.2766602 1.5362670 7 MeanX1 M 1 x1 0.9848940 0.03743404 0.9010513 1.0645530 8 MeanX2 M 1 x2 1.9741801 0.04444123 1.8710743 2.0624128 9 MeanY M 1 y 2.5530358 0.07517496 2.3998888 2.6843375 Model Statistics: | Parameters | Degrees of Freedom | Fit (-2lnL units) Model: 9 1491 3010.73 Saturated: 9 1491 NA Independence: 6 1494 NA Number of observations/statistics: 500/1500 Information Criteria: | df Penalty | Parameters Penalty | Sample-Size Adjusted AIC: 28.73015 3028.730 3029.097 BIC: -6255.25053 3066.662 3038.095 CFI: NA TLI: 1 (also known as NNFI) RMSEA: 0 [95% CI (NA, NA)] Prob(RMSEA <= 0.05): NA To get additional fit indices, see help(mxRefModels) timestamp: 2018-04-07 12:35:46 Wall clock time: 0.602927 secs OpenMx version number: 2.9.6 Need help? See help(mxSummary) SE 2.5% 97.5% [1,] 0.06605965 -0.1085388 0.149956 SE 25.0% 75.0% [1,] 0.06605965 -0.01632241 0.05732906