R Under development (unstable) (2023-07-07 r84657 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(testthat) > library(betaDelta) > > test_check("betaDelta") Call: BetaDelta(object = object, type = "adf") Standardized regression slopes with ADF standard errors: Call: BetaDelta(object = object, type = "adf") Standardized regression slopes with ADF standard errors: Call: BetaDelta(object = object, type = "mvn") Standardized regression slopes with MVN standard errors: est se t df p 0.05% 0.5% 2.5% 97.5% 99.5% NARTIC 0.4951 0.0759 6.5272 42 0.000 0.2268 0.2905 0.3421 0.6482 0.6998 PCTGRT 0.3915 0.0770 5.0824 42 0.000 0.1190 0.1837 0.2360 0.5469 0.5993 PCTSUPP 0.2632 0.0747 3.5224 42 0.001 -0.0011 0.0616 0.1124 0.4141 0.4649 99.95% NARTIC 0.7635 PCTGRT 0.6640 PCTSUPP 0.5276 Call: BetaDelta(object = object, type = "mvn") Standardized regression slopes with MVN standard errors: Call: BetaDelta(object = object, type = "adf") Standardized regression slopes with ADF standard errors: est se t df p 0.05% 0.5% 2.5% 97.5% 99.5% NARTIC 0.4951 0.0674 7.3490 42 0.0000 0.2568 0.3134 0.3592 0.6311 0.6769 PCTGRT 0.3915 0.0710 5.5164 42 0.0000 0.1404 0.2000 0.2483 0.5347 0.5830 PCTSUPP 0.2632 0.0769 3.4231 42 0.0014 -0.0088 0.0558 0.1081 0.4184 0.4707 99.95% NARTIC 0.7335 PCTGRT 0.6426 PCTSUPP 0.5353 Call: BetaDelta(object = object, type = "adf") Standardized regression slopes with ADF standard errors: Call: BetaDelta(object = object, type = "mvn") Standardized regression slopes with MVN standard errors: est se t df p 0.05% 0.5% 2.5% 97.5% 99.5% 99.95% NARTIC 0.7622 0.0618 12.3341 44 0 0.5443 0.5958 0.6376 0.8867 0.9285 0.98 Call: BetaDelta(object = object, type = "mvn") Standardized regression slopes with MVN standard errors: Call: BetaDelta(object = object, type = "adf") Standardized regression slopes with ADF standard errors: est se t df p 0.05% 0.5% 2.5% 97.5% 99.5% 99.95% NARTIC 0.7622 0.0604 12.625 44 0 0.5493 0.5996 0.6405 0.8838 0.9247 0.975 Call: BetaDelta(object = object, type = "adf") Standardized regression slopes with ADF standard errors: Call: BetaDelta(object = object, type = "mvn") Standardized regression slopes with MVN standard errors: Call: BetaDelta(object = object, type = "mvn") Standardized regression slopes with MVN standard errors: Call: DiffBetaDelta(object = BetaDelta(object, type = "mvn")) Difference between standardized regression coefficients with MVN standard errors: est se z p 0.05% 0.5% 2.5% 97.5% NARTIC-PCTGRT 0.1037 0.1357 0.7640 0.4449 -0.3428 -0.2458 -0.1623 0.3696 NARTIC-PCTSUPP 0.2319 0.1252 1.8524 0.0640 -0.1800 -0.0906 -0.0135 0.4773 PCTGRT-PCTSUPP 0.1282 0.1227 1.0451 0.2960 -0.2755 -0.1878 -0.1123 0.3688 99.5% 99.95% NARTIC-PCTGRT 0.4531 0.5501 NARTIC-PCTSUPP 0.5544 0.6438 PCTGRT-PCTSUPP 0.4443 0.5320 Call: DiffBetaDelta(object = BetaDelta(object, type = "mvn")) Difference between standardized regression coefficients with MVN standard errors: Call: DiffBetaDelta(object = BetaDelta(object, type = "adf")) Difference between standardized regression coefficients with ADF standard errors: est se z p 0.05% 0.5% 2.5% 97.5% NARTIC-PCTGRT 0.1037 0.1212 0.8555 0.3923 -0.2950 -0.2084 -0.1338 0.3411 NARTIC-PCTSUPP 0.2319 0.1181 1.9642 0.0495 -0.1566 -0.0722 0.0005 0.4633 PCTGRT-PCTSUPP 0.1282 0.1215 1.0555 0.2912 -0.2716 -0.1847 -0.1099 0.3664 99.5% 99.95% NARTIC-PCTGRT 0.4158 0.5024 NARTIC-PCTSUPP 0.5360 0.6204 PCTGRT-PCTSUPP 0.4412 0.5281 Call: DiffBetaDelta(object = BetaDelta(object, type = "adf")) Difference between standardized regression coefficients with ADF standard errors: [ FAIL 0 | WARN 0 | SKIP 0 | PASS 16 ] > > proc.time() user system elapsed 1.03 0.21 1.25