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When testing bain in JASP we came across the following inconsistencies in the results. Maybe you have an idea where this originates and how to tackle these differences.
Windows/Mac
data("sesamesim")
formula <- age ~ site + peabody + prenumb + postnumb + funumb - 1
hypothesis <- "site1 = site2 = site3 = site4 = site5;site1 < site2 < site3 < site4 < site5;site1 > site2 > site3 > site4 > site5"
fraction <- 1
standardized <- FALSE
sesamesim$site <- factor(sesamesim$site)
fit <- stats::lm(formula = formula, data = sesamesim)
bainResult <- bain::bain(x = fit, hypothesis = hypothesis, fraction = fraction, standardize = standardized)
> print(bainResult)
Bayesian informative hypothesis testing for an object of class lm (ANCOVA):
Fit Com BF.u BF.c PMPa PMPb
H1 0.000 0.000 0.000 0.000 0.015 0.000
H2 0.000 0.007 0.007 0.007 0.985 0.007
H3 0.000 0.007 0.000 0.000 0.000 0.000
Hu 0.993
Hypotheses:
H1: site1=site2=site3=site4=site5
H2: site1<site2<site3<site4<site5
H3: site1>site2>site3>site4>site5
Note: BF.u denotes the Bayes factor of the hypothesis at hand versus the unconstrained hypothesis Hu. BF.c denotes the Bayes factor of the hypothesis at hand versus its complement.
> bainResult$BFmatrix
H1 H2 H3
H1 1.000000000 1.476255e-02 30175.92
H2 67.738958866 1.000000e+00 2044085.52
H3 0.000033139 4.892163e-07 1.00
Linux
data("sesamesim")
formula <- age ~ site + peabody + prenumb + postnumb + funumb - 1
hypothesis <- "site1 = site2 = site3 = site4 = site5;site1 < site2 < site3 < site4 < site5;site1 > site2 > site3 > site4 > site5"
fraction <- 1
standardized <- FALSE
sesamesim$site <- factor(sesamesim$site)
fit <- stats::lm(formula = formula, data = sesamesim)
bainResult <- bain::bain(x = fit, hypothesis = hypothesis, fraction = fraction, standardize = standardized)
> print(bainResult)
Bayesian informative hypothesis testing for an object of class lm (ANCOVA):
Fit Com BF.u BF.c PMPa PMPb
H1 0.000 0.000 0.000 0.000 0.014 0.000
H2 0.000 0.007 0.007 0.007 0.986 0.007
H3 0.000 0.006 0.000 0.000 0.000 0.000
Hu 0.992
Hypotheses:
H1: site1=site2=site3=site4=site5
H2: site1<site2<site3<site4<site5
H3: site1>site2>site3>site4>site5
Note: BF.u denotes the Bayes factor of the hypothesis at hand versus the unconstrained hypothesis Hu. BF.c denotes the Bayes factor of the hypothesis at hand versus its complement.
> bainResult$BFmatrix
H1 H2 H3
H1 1.000000e+00 1.404837e-02 22430.45
H2 7.118265e+01 1.000000e+00 1596659.07
H3 4.458225e-05 6.263078e-07 1.00
As you can see, the results between Mac/Windows and Linux diverge (for example BF23 = 30175.92 on windows versus BF23 = 22430.45 on Linux).
The text was updated successfully, but these errors were encountered:
@koenderks I'm pretty sure this is due to the different implementation of the random number generator at the OS level. I don't think any action is required/possible. Have you any further insight?
When testing bain in JASP we came across the following inconsistencies in the results. Maybe you have an idea where this originates and how to tackle these differences.
Windows/Mac
Linux
As you can see, the results between Mac/Windows and Linux diverge (for example BF23 = 30175.92 on windows versus BF23 = 22430.45 on Linux).
The text was updated successfully, but these errors were encountered: