Fix snapshot differences (it may need muting h_ppmeans())
#1072
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This is not used in BAC AFAIK 👍🏼 |
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Code Coverage SummaryDiff against mainResults for commit: f9c5826 Minimum allowed coverage is ♻️ This comment has been updated with latest results |
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In TLG-C, See context: ...
) %>%
summarize_glm_count(
vars = "AVAL",
variables = list(arm = "ARM", offset = "lgTMATRSK", covariates = NULL),
conf_level = 0.95,
distribution = "poisson",
rate_mean_method = "emmeans",
var_labels = "Unadjusted exacerbation rate (per year)",
table_names = "unadj",
.stats = c("rate"),
.labels = c(rate = "Rate")
) %>%
summarize_glm_count(
vars = "AVAL",
variables = list(arm = "ARM", offset = "lgTMATRSK", covariates = c("REGION1")),
conf_level = 0.95,
distribution = "quasipoisson",
rate_mean_method = "ppmeans",
var_labels = "Adjusted (QP) exacerbation rate (per year)",
table_names = "adj",
.stats = c("rate", "rate_ci", "rate_ratio", "rate_ratio_ci", "pval"),
.labels = c(
rate = "Rate", rate_ci = "Rate CI", rate_ratio = "Rate Ratio",
rate_ratio_ci = "Rate Ratio CI", pval = "p value"
)
) |
BFalquet
approved these changes
Oct 2, 2023
Melkiades
commented
Oct 2, 2023
| @@ -186,6 +187,7 @@ testthat::test_that("h_ppmeans works with healthy input", { | |||
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| testthat::expect_snapshot(fits2) | |||
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| # XXX ppmeans fails snapshot diff in integration tests | |||
| result <- h_ppmeans( | |||
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Keeping this failing to see if set.seed helps and if also AVR is triggered by this change
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Fixes #1058
The error comes ONLY from integration tests (mismatch of output rates and rate CI in
h_ppmeans()). @ayogasekaram tested on docker image, @edelarua and I tested it (I think window-based rstudio and Ubuntu rstudio-server) and there are no differences in our snapshots, i.e. it is passing for all of us. Now I think this needs to come fromstats::predictstep inh_ppmeansas also rates are different. It seems we tested everything (adding random seed does not change my local snapshots). Could it have something to do with the system libraries? what do you think @cicdguy? If we cannot fix it, and it is not a fundamental feature we might want to turn it off. Is this function used in the biomarker catalog @danielinteractive? To my knowledge, it is not used in the TLG-c, right @ayogasekaram @edelarua?Please refer to #1059 and integration tests for the changes that exclude the fit itself from having any changes local vs integration tests.