Nothing
tests/testthat/test-0-CRAN.R
In RoBMA: Robust Bayesian Meta-Analyses
context("(0) Basic tests for CRAN")
# These are just a very rudimentary tests that don't require time or saved files.
# The full range of tests is run locally.
test_that("Basic functionality works", {
RoBMA:::.load_RoBMA_module()
# fit a default model
d <- c(0.1, 0.2, 0.3)
n <- c(20, 15, 10)
fit_default <- suppressWarnings(RoBMA(d = d, n = n, chains = 1, burnin = 50, sample = 100, autofit = FALSE, seed = 1))
expect_equal(TRUE, is.RoBMA(fit_default))
expect_equal(
capture_output_lines(fit_default, print = TRUE, width = 150),
c("Call:" ,
"RoBMA(d = d, n = n, chains = 1, sample = 100, burnin = 50, autofit = FALSE, " ,
" seed = 1)" ,
"" ,
"Estimates:" ,
" mu tau omega[0,0.025] omega[0.025,0.05] omega[0.05,0.5] omega[0.5,0.95] omega[0.95,0.975] omega[0.975,1] ",
" -0.003244705 0.088661462 1.000000000 0.946723035 0.866019085 0.760510379 0.765383672 0.781386929 ",
" PET PEESE " ,
" 0.044580252 0.045223594 " )
)
expect_equal(
capture_output_lines(summary(fit_default), print = TRUE, width = 150),
c("Call:" ,
"RoBMA(d = d, n = n, chains = 1, sample = 100, burnin = 50, autofit = FALSE, " ,
" seed = 1)" ,
"" ,
"Robust Bayesian meta-analysis" ,
"Components summary:" ,
" Models Prior prob. Post. prob. Inclusion BF" ,
"Effect 18/36 0.500 0.288 0.405" ,
"Heterogeneity 18/36 0.500 0.412 0.702" ,
"Bias 32/36 0.500 0.460 0.852" ,
"" ,
"Model-averaged estimates:" ,
" Mean Median 0.025 0.975" ,
"mu -0.003 0.000 -0.613 0.606" ,
"tau 0.089 0.000 0.000 0.514" ,
"omega[0,0.025] 1.000 1.000 1.000 1.000" ,
"omega[0.025,0.05] 0.947 1.000 0.470 1.000" ,
"omega[0.05,0.5] 0.866 1.000 0.238 1.000" ,
"omega[0.5,0.95] 0.761 1.000 0.017 1.000" ,
"omega[0.95,0.975] 0.765 1.000 0.017 1.000" ,
"omega[0.975,1] 0.781 1.000 0.017 1.000" ,
"PET 0.045 0.000 0.000 0.641" ,
"PEESE 0.045 0.000 0.000 0.614" ,
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale).",
"(Estimated publication weights omega correspond to one-sided p-values.)" ,
"\033[0;31mModel (2): ESS 45 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (3): ESS 39 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (4): ESS 29 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (5): ESS 36 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (6): ESS 28 is lower than the set target (500).\033[0m" ,
"\033[0;31mThere were another 29 warnings. To see all warnings call 'check_RoBMA(fit)'.\033[0m")
)
df_reg <- data.frame(
d = d,
se = se_d(d, n),
mod_con = scale(1:3),
mod_cat = c("A", "A", "B")
)
fit_reg <- suppressWarnings(RoBMA.reg(~ mod_cat + mod_con, data = df_reg, priors_bias = NULL, chains = 1, burnin = 50, sample = 100, autofit = FALSE, seed = 1))
expect_equal(
capture_output_lines(summary(fit_reg), print = TRUE, width = 150),
c("Call:" ,
"RoBMA.reg(formula = ~mod_cat + mod_con, data = df_reg, priors_bias = NULL, " ,
" chains = 1, sample = 100, burnin = 50, autofit = FALSE, seed = 1)" ,
"" ,
"Robust Bayesian meta-regression" ,
"Components summary:" ,
" Models Prior prob. Post. prob. Inclusion BF" ,
"Effect 8/16 0.500 0.267 0.364" ,
"Heterogeneity 8/16 0.500 0.401 0.671" ,
"" ,
"Meta-regression components summary:" ,
" Models Prior prob. Post. prob. Inclusion BF" ,
"mod_cat 8/16 0.500 0.470 0.886" ,
"mod_con 8/16 0.500 0.446 0.805" ,
"" ,
"Model-averaged estimates:" ,
" Mean Median 0.025 0.975" ,
"mu 0.048 0.000 -0.300 0.667" ,
"tau 0.094 0.000 0.000 0.581" ,
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale).",
"\033[0;31mModel (2): ESS 44 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (3): ESS 45 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (4): ESS 58 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (5): ESS 4 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (6): ESS 6 is lower than the set target (500).\033[0m" ,
"\033[0;31mThere were another 9 warnings. To see all warnings call 'check_RoBMA(fit)'.\033[0m" ,
"" ,
"Model-averaged meta-regression estimates:" ,
" Mean Median 0.025 0.975" ,
"intercept 0.048 0.000 -0.300 0.667" ,
"mod_cat [dif: A] 0.000 0.000 -0.357 0.459" ,
"mod_cat [dif: B] 0.000 0.000 -0.459 0.357" ,
"mod_con 0.005 0.000 -0.341 0.343" ,
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale).",
"\033[0;31mModel (2): ESS 44 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (3): ESS 45 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (4): ESS 58 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (5): ESS 4 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (6): ESS 6 is lower than the set target (500).\033[0m" ,
"\033[0;31mThere were another 9 warnings. To see all warnings call 'check_RoBMA(fit)'.\033[0m"
))
})
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RoBMA documentation built on July 26, 2023, 5:13 p.m.
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context("(0) Basic tests for CRAN")
# These are just a very rudimentary tests that don't require time or saved files.
# The full range of tests is run locally.
test_that("Basic functionality works", {
RoBMA:::.load_RoBMA_module()
# fit a default model
d <- c(0.1, 0.2, 0.3)
n <- c(20, 15, 10)
fit_default <- suppressWarnings(RoBMA(d = d, n = n, chains = 1, burnin = 50, sample = 100, autofit = FALSE, seed = 1))
expect_equal(TRUE, is.RoBMA(fit_default))
expect_equal(
capture_output_lines(fit_default, print = TRUE, width = 150),
c("Call:" ,
"RoBMA(d = d, n = n, chains = 1, sample = 100, burnin = 50, autofit = FALSE, " ,
" seed = 1)" ,
"" ,
"Estimates:" ,
" mu tau omega[0,0.025] omega[0.025,0.05] omega[0.05,0.5] omega[0.5,0.95] omega[0.95,0.975] omega[0.975,1] ",
" -0.003244705 0.088661462 1.000000000 0.946723035 0.866019085 0.760510379 0.765383672 0.781386929 ",
" PET PEESE " ,
" 0.044580252 0.045223594 " )
)
expect_equal(
capture_output_lines(summary(fit_default), print = TRUE, width = 150),
c("Call:" ,
"RoBMA(d = d, n = n, chains = 1, sample = 100, burnin = 50, autofit = FALSE, " ,
" seed = 1)" ,
"" ,
"Robust Bayesian meta-analysis" ,
"Components summary:" ,
" Models Prior prob. Post. prob. Inclusion BF" ,
"Effect 18/36 0.500 0.288 0.405" ,
"Heterogeneity 18/36 0.500 0.412 0.702" ,
"Bias 32/36 0.500 0.460 0.852" ,
"" ,
"Model-averaged estimates:" ,
" Mean Median 0.025 0.975" ,
"mu -0.003 0.000 -0.613 0.606" ,
"tau 0.089 0.000 0.000 0.514" ,
"omega[0,0.025] 1.000 1.000 1.000 1.000" ,
"omega[0.025,0.05] 0.947 1.000 0.470 1.000" ,
"omega[0.05,0.5] 0.866 1.000 0.238 1.000" ,
"omega[0.5,0.95] 0.761 1.000 0.017 1.000" ,
"omega[0.95,0.975] 0.765 1.000 0.017 1.000" ,
"omega[0.975,1] 0.781 1.000 0.017 1.000" ,
"PET 0.045 0.000 0.000 0.641" ,
"PEESE 0.045 0.000 0.000 0.614" ,
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale).",
"(Estimated publication weights omega correspond to one-sided p-values.)" ,
"\033[0;31mModel (2): ESS 45 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (3): ESS 39 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (4): ESS 29 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (5): ESS 36 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (6): ESS 28 is lower than the set target (500).\033[0m" ,
"\033[0;31mThere were another 29 warnings. To see all warnings call 'check_RoBMA(fit)'.\033[0m")
)
df_reg <- data.frame(
d = d,
se = se_d(d, n),
mod_con = scale(1:3),
mod_cat = c("A", "A", "B")
)
fit_reg <- suppressWarnings(RoBMA.reg(~ mod_cat + mod_con, data = df_reg, priors_bias = NULL, chains = 1, burnin = 50, sample = 100, autofit = FALSE, seed = 1))
expect_equal(
capture_output_lines(summary(fit_reg), print = TRUE, width = 150),
c("Call:" ,
"RoBMA.reg(formula = ~mod_cat + mod_con, data = df_reg, priors_bias = NULL, " ,
" chains = 1, sample = 100, burnin = 50, autofit = FALSE, seed = 1)" ,
"" ,
"Robust Bayesian meta-regression" ,
"Components summary:" ,
" Models Prior prob. Post. prob. Inclusion BF" ,
"Effect 8/16 0.500 0.267 0.364" ,
"Heterogeneity 8/16 0.500 0.401 0.671" ,
"" ,
"Meta-regression components summary:" ,
" Models Prior prob. Post. prob. Inclusion BF" ,
"mod_cat 8/16 0.500 0.470 0.886" ,
"mod_con 8/16 0.500 0.446 0.805" ,
"" ,
"Model-averaged estimates:" ,
" Mean Median 0.025 0.975" ,
"mu 0.048 0.000 -0.300 0.667" ,
"tau 0.094 0.000 0.000 0.581" ,
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale).",
"\033[0;31mModel (2): ESS 44 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (3): ESS 45 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (4): ESS 58 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (5): ESS 4 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (6): ESS 6 is lower than the set target (500).\033[0m" ,
"\033[0;31mThere were another 9 warnings. To see all warnings call 'check_RoBMA(fit)'.\033[0m" ,
"" ,
"Model-averaged meta-regression estimates:" ,
" Mean Median 0.025 0.975" ,
"intercept 0.048 0.000 -0.300 0.667" ,
"mod_cat [dif: A] 0.000 0.000 -0.357 0.459" ,
"mod_cat [dif: B] 0.000 0.000 -0.459 0.357" ,
"mod_con 0.005 0.000 -0.341 0.343" ,
"The estimates are summarized on the Cohen's d scale (priors were specified on the Cohen's d scale).",
"\033[0;31mModel (2): ESS 44 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (3): ESS 45 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (4): ESS 58 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (5): ESS 4 is lower than the set target (500).\033[0m" ,
"\033[0;31mModel (6): ESS 6 is lower than the set target (500).\033[0m" ,
"\033[0;31mThere were another 9 warnings. To see all warnings call 'check_RoBMA(fit)'.\033[0m"
))
})
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Any scripts or data that you put into this service are public.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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